K-means method. Taking these clusters and task performances into account, the general cognitive state of each participant was classified as low risk or high risk. Logistic Regression, Decision Tree, and Neural Networks were also used to classify the same data in order to measure the consistency of this classification with other techniques and the method provided a consistency between 87.1% and 100% with other techniques.Brain-Computer Interfaces (BCI) are systems originally developed to assist paralyzed patients allowing for commands to the computer with brain activities. This study aims to examine cognitive state with an objective, easy-to-use, and easy-to-interpret method utilizing Brain-Computer Interface systems. Seventy healthy participants completed six tasks using a Brain-Computer Interface system and participants' pupil dilation, blink rate, and Galvanic Skin Response (GSR) data were collected simultaneously. Participants filled Nasa-TLX forms following each task and task performances of participants were also measured. Cognitive state clusters were created from the data collected using the  One of the most important issues which ergonomics addresses is the reduction of human errors and accidents. Human errors may have serious consequences from system disruptions to loss of life. Considering that humans have limited capacities both physically and mentally, it is evidently an important necessity to create designs appropriate for human capacity regardless of the task. In-depth studies on human's physical capacity have been performed and are still being performed. For physical fatigue, measurement and calculation methods have been developed, which have general validity in numerous subjects such as muscle fatigue, rest period, and audiovisual capabilities. However, although it is known that humans have limited mental capacities as well, a method determining mental fatigue and mental performance accurately is not available yet. Although there are some accepted methods predicting the cognitive load caused by the task at hand, strengths and weaknesses of these methods are open to dispute.On the other hand, it is not possible to explain the mental aspect of human errors solely with cognitive load. Although excessive cognitive load is a cause for error, factors which make it more difficult to maintain attention during performance such as extreme stress, mind wandering, and drowsiness due to monotony should also be considered. For this reason, in addition to ongoing studies on measurement of cognitive load, researchers show an interest in the concept of cognitive state as well, which is usually determined with more than one measure.Within the scope of this study, we performed an experimental study based on the use of some of the methods used in prediction of cognitive load and cognitive state and utilizing BCI systems. BCI systems were utilized for experiments. The idea was to use the ability of giving commands to the computer with brain activities of these systems originally developed for medical purposes and have the participants complete tasks during experiments in this way. 70 students attending Osmangazi University participated in the experiment and completed tasks designed with the Brain-Computer Interface (BCI). Subjective and objective data collected from each participant were evaluated to make a cognitive state classification and a risk identification method was proposed based on instantaneous cognitive states of individuals.BCI systems have the potential to facilitate life for those who have severely damaged motor skills in accordance with their primary purpose. At this point, all BCI applications, especially Motor Imagery, are beneficial . The useOn the other hand, cognitive load detection, cognitive state monitoring, and attention performance are on the forefront of the use of BCI systems in nonmedical areas . It is pIn their experimental study, Schultheis and Jameson  used theIn their study, Roy et al.  stated tChuang et al.  designedHashemi et al.  performeRozado et al.  examinedMyrden and Chau  investigIn their study, Lim et al.  reportedAlthough studies on nonmedical use of BCI systems have increased in number in recent years, experimental studies comprehensively using all features of BCI systems have not been conducted yet. From this point, we designed an experimental study containing tasks requiring different brain activities and different cognitive states and requiring individuals to complete tasks with different difficulty levels creating both a drowsiness effect and cognitive loading.The participants completed tasks using the g.tec BCI system in this study. In addition, a GSR measurement tool and the Tobii X2-60 eye tracker were used in order to measure pupil diameter remotely. For all the tasks, the same 17′′ laptop computer was used.Seventy students between the ages of 18–35 participated in the experiment on a voluntary basis. 40 participants were female and 30 participants were male. All of the participants were undergraduate or graduate students at Industrial Engineering Department, Osmangazi University. 64 participants were undergraduate students, whereas 6 participants were graduate students. Also, 9 participants had full- or part-time jobs in addition to their studies. Additionally, 28 participants had an ECTS credit load over 30, 8 participants had a Grade Point Average (GPA) below 2.00, 51 had a GPA between 2.00 and 3.00, and 11 had a GPA of 3.00 or above.Change in pupil diameterBlink rateGalvanic Skin ResponseIt was possible to assess the SSVEP potential as a support to the P300 potential, which is one of the potentials associated with cognitive load most frequently, and the Motor Imagery application with the BCI system used in the study. The following physiological data were measured and recorded simultaneously in order to predict how much difficulty the participants had while completing the tasks by giving commands to the computer with brain activities:We asked the participants to complete the tasks in BCI applications and conducted classification and prediction studies based on mental loading data during these tasks in order to determine their current cognitive state and performance in tasks requiring attention and mental effort in this state. In experiments, the participants completed three BCI applications twice, each with different parameters and difficulty levels, with 2- to 5-minute rest periods . Participants filled the Nasa-TLX form after each application. Also, signal controls were performed before each BCI application.In order to calculate the change in pupil diameter, the average diameter in the first 1 second of the task was used as the base value and the average value in the remainder of the task was proportional to this base value. To find the blink rate, records taken by the eye tracker with 17-millisecond intervals were used. Instants when the data related to eye movements were missing  were accepted as instants of blinking and these lines were counted to find the blink rate.The data normalized with the method proposed by Nourbakhsh et al.  were useThe BCI system used in the study creates the P300 potential via visual stimuli. A character matrix is used for this and the participants spell words on the screen via this matrix. The spelling of the target character is made possible by the recurring emergence of the P300 potential. Before starting this task, we had the participants spell a random character on the screen initially to familiarize the participants with the matrix. Then, the participants were given the task of spelling two words. The first task to complete in this study was defined as spelling the characters ABCDE, which were side by side on the matrix. During this task, the number of visual stimuli sent by target characters, that is, flashing, was set to 30. The length of visual stimulus was set to 100 milliseconds. Also, the character duplication method was used in this first task. Accordingly, target characters were shown on the screen and the place of the target character was shown to the participants by flashing by itself for a second initially. The free spelling method was used in the second task. In other words, the character to be spelled by the participant was not shown on the screen. Also, flashing count was set to 10 and flashing length was set to 50 milliseconds in order to have the participants make more effort. The array of characters to be spelled on the screen in the second task was determined to be ESOGU2014. This task was explained to the participants only verbally. Thus, the participants had to remember the order of the characters and find the place of the relevant character on the matrix on his/her own. The SSVEP potential occurs by focusing on stimuli with fixed visual frequency. To this end, LEDs representing directions need to flash on a box showing up, down, right, and left and the participants need to follow stimuli coming from the target direction. The participants had to complete two tasks, the first requiring a shorter focus and the second requiring a longer focus. Difficulty levels of the tasks were set by changing the length and interval of the stimuli. The participants focused on LEDs flashing in the order of left, up, right, and down in the first task. There were 10.5 seconds between two directions. In the first task, 70% of these 10.5 seconds were determined as stimulus length and the remaining 30% were waiting period in transitions between two directions. In the second iteration, the visual stimulus length was set to 95% and the transition time was set to 5% to ensure longer focus time and faster transition. SSVEP control device can be seen in x-axis on the x-y plain on the screen. A red arrow appearing on the x-axis once in 7 seconds shows the participants which direction (right and left) to focus on. The participants focus on moving the hand on the target direction for 7 seconds; however, they do not make an actual motion with their hands. After 20 iterations in the first task, the second Motor Imagery task started. This time, an additional blue arrow providing feedback to the participants was also present. The blue arrow appearing once the red arrow shows the direction moves to the correct or the opposite direction depending on the participants' focusing success. A screenshot of Motor Imagery task is presented as Essentially, Motor Imagery is an event-related desynchronization/synchronization (ERD/ERS) occurring in the brain. The participants are guided by the The main purpose of the study is to give an opinion about the cognitive state of an individual to complete a task requiring mental effort  and attention before said task and performance of the individual during said task. A summary of task properties is presented in t-test. The results are shown in t-test analyses.Nasa-TLX scores were used to evaluate difficulty levels of tasks completed. Nasa-TLX scores showed a normal distribution in at least one normality test and thus were analyzed with paired Task performances of the participants  were assK-means algorithm can be listed as a nonhierarchical method.Data mining is a collection of methods used to extract important data by analyzing large data sets, which allows for obtaining and interpreting information . It is cK-means method using physiological measurement data. A classification method was proposed taking task performances of participants in these clusters into account. It was expected that the proposed method would be a flexible, multidimensional, and comprehensive tool for BCI studies that can include implementations addressing various cognitive states and brain activities. The steps of the proposed method are as follows:Collecting physiological data in order to interpret cognitive state.Determining Silhouette scores in order to achieve clusters of 2, 3, and 4 with this data .Selecting the cluster number with the best score and tagging these clusters by interpreting in terms of cognitive state.Dividing task performances into at least two classes.Assessing cognitive states and task performances and determining individuals in the positive class in both.Within the scope of this study, the participants were clustered with the The cluster indicating a higher cognitive loading for P300 tasks, which mostly require cognitive effort, was tagged as the risky cluster.Since the main risk was monotony for the SSVEP task due to its nature, the group where physiological indicators opposite to cognitive loading concentrated was tagged as risky.Since the cognitive demand was lower and the concentration requirement was higher in the Motor Imagery/1 task, the cluster showing a tendency opposite to cognitive loading was tagged as the risky cluster.Since the Motor Imagery/2 task had an indicator providing instantaneous feedback during concentration and followed constantly, which resulted in more sources requiring cognitive effort, the group showing a cognitive loading tendency was tagged as risky.In case all physiological indicators supported the interpretation when interpreting clusters, the pupil diameter change was used as base, because it showed significant differences both between different difficulty levels of the same task and between different task types in previous statistical analyses and stood out as the most sensitive physiological measure.Clusters of 2 were interpreted according to cognitive effort required by the task and cognitive state expected to pose a risk:For all tasks, clusters which seemed more risky were tagged with 0 and clusters which seemed less risky were tagged with 1 taking expected physiological outcomes into account .Individuals' cognitive states and task performances were considered to determine task risk classes. The combination of Risk-free Cognitive State-High Performance (70% success at least) was required for the low-risk class. All other combinations were assigned to the high-risk class. In this way, the participants whose cognitive state posed a low risk due to the properties of the task and whose task performance was high in tasks requiring constant attention and concentration were accepted to be low-risk for mental-weighted tasks in general.Risk classes of all 6 tasks were taken into account in determination of general risk classes. In this classification, the 50% cut-off condition, also used in classification with Logistic Regression, was applied; that is, those who were in the low-risk group for 3 or more of 6 tasks were assigned to the low general risk class. Those who did not meet this condition were assigned to the high general risk class. Thus, 59 out of 70 participants were assigned to the high-risk class, whereas 11 participants were assigned to the low-risk class.R2 value was found to be 1.0; that is, the model explained the variance in the dependent variable (risk classes) completely. According to the results of the Omnibus test  method assigned a high risky participant to the low-risk class. When the data of this participant were examined, it was seen that the participant achieved high success in the tasks of P300 and SSVEP compared to average performance. In the case of all the remaining inconsistent classifications, low risky participants were assigned to the high-risk class. When these participants' data were examined, it was observed that their pupil dilations were dominant especially for P300 and SSVEP tasks.Errors and accidents caused by human error may occur in every area of life. These errors may have more serious consequences for both human health and performance of the system in areas such as production or transportation. Human error has more than one dimension. These dimensions include the design and conditions of the working environment, physical fatigue, mental fatigue, person's cognitive state, and job's cognitive requirements. The factor which is the most difficult to monitor and detect is person's cognitive state. Cognitive state leads to risks at different levels depending on the job such as excessive cognitive loading, drowsiness due to job's monotony, distraction, and lack of concentration. Most studies in this field focus on detection of drowsiness of vehicle drivers. In addition, various approaches are discussed in studies on detection of cognitive load and mental fatigue.Although there are methods with an accepted general validity such as Nasa-TLX among subjective methods, the need for stronger tools has encouraged researchers to find new ways. Behavioral measures such as monitoring task performance and monitoring physical indicators related to autonomous nervous system have emerged as alternatives as a result of this search. Particularly physiological indicators related to autonomous nervous system are of great interest due to their objective nature. Physiological methods such as heart rate variability, respiration rate, pupil diameter changes, blink rate and duration, and Galvanic Skin Response stand out in studies on detection of cognitive load and cognitive state. On the other hand, brain activities are preferred to collect data more directly. The fact that developing technology allows not only for tracking brain waves, but also for imaging brain activities in detail has steered studies to this direction. Again with the effect of developing technology, the possibility of tracking a measure with proven sensitivity such as pupil diameter rapidly and accurately provides a great advantage for researchers in this field.Although the number of methods and devices to use to track physiological indicators and brain activities increases, this does not resolve the complexity of interpreting physiological indicators in particular. Such indicators and activities are affected from environmental factors very quickly, and thus data collection and interpretation are more possible in controlled laboratory environments. In particular, interpreting brain activities requires expertise and it is not easy to use brain activities in studies aimed directly at working life.At this point, Brain-Computer Interfaces which were originally developed to facilitate the lives of stroke patients and allow for controlling computers and devices with brain activities are of great interest for researchers conducting cognitive studies. These interfaces which can be used with certain special brain activities have begun to be used in cognitive state and cognitive state detection studies in recent years. Detecting whether the relevant brain activity directly occurs via interfaces apart from the signal data means easier interpretation of data provided by these devices.Six tasks were developed using a BCI system within the scope of this study and data related to pupil diameter, blink rate, and normalized GSR were recorded simultaneously. In this way, we ensured that tasks directly requiring attention and concentration were completed directly with brain activities and advantages of both physiological measurements and behavioral measurements were drawn together. Nasa-TLX, the best known subjective method, was used as supplement.K-means technique was used in clustering analyses and it was found with the help of Silhouette scores that the strongest clustering was obtained when the cluster count was 2. After forming clusters with physiological data of the participants for each task, the clusters were examined individually and the participants' states such as cognitive load, drowsiness, and concentration were interpreted. The participants' expected cognitive state due to the nature of the task and the expected physiological effects of these states were taken into account when making these interpretations.The data were clustered in later steps. The Once clusters were formed and participants in the negative group and the positive group were tagged for each task, cognitive risk classes were created for each task. At this stage, cognitive states and BCI task performances of the participants were compared. Those who had both a positive cognitive state and a high task performance were assigned to the positive cognitive risk class. Those with negative cognitive state and/or low task performance were assigned to the negative cognitive risk class. Thus, task performances of the participants in tasks requiring attention and their cognitive states when performing these tasks were considered together. General risk classes, on the other hand, were created by seeking a 50% cut-off condition in cognitive risk classes created for 6 tasks. Those who were assigned to the positive cognitive risk class in at least 3 of 6 tasks were assigned to the positive (low-risk) general risk class. Those who did not meet this condition were assigned to high general risk class.At the next stage, this risk classification was compared to other classification methods. Two trials (cut-off conditions 50% and 70%) with Binary Logistic Regression, the first of these methods, provided 100% consistency. The Decision Tree method, the second of these methods, was tested with 3 different algorithms provided by SPSS 22 package program. One of these algorithms, the CRT algorithm, showed 100% consistency with our classification. The last classification method was the Artificial Neural Networks method. The classification made with the Batch training method by the Artificial Neural Network created with 100% training data provided 100% consistency.This study constitutes an example for nonmedical use of BCI systems. This experimental method preserving the reliability of brain activities in studies on cognitive state by removing the interpretation difficulty was also supported by physiological indicators. Another advantage of the method was that the tasks performed during the experiment were independent of skill levels of the participants and completed directly with brain activities.BCI systems are expected to be used much more frequently in studies on cognitive loading and cognitive state in the near future. The flexibility of these systems makes it possible to sector- and purpose-specific interfaces. It is also possible to create authentic simulation environments by integrating BCI systems with three-dimensional virtual environments. Ease of application and interpretation of these systems indicates that they will find their place in working life.


Background: Considering the renewed emphasis on women’s health, attention to the new aspects of their health, such as equity, among different groups is warranted. The aim of this study was to investigate the economic inequalities among women with osteoporosis-related bone fractures (ORBFs) in Sanandaj, Iran.Methods: In this cross-sectional study, convenient sampling was employed to recruit 220 women with osteoporosis referring to the only rheumatology clinic in Sanandaj (the center of Kurdistan province in Iran) from January to April 2013. Main outcome was the history of fractures due to osteoporosis. Concentration index decomposition (CID) and logistic regression were used for data analysis. Results: In multivariate logistic analysis, the fourth and fifth quintiles of family economic status were found to be significantly associated with ORBFs. Risk difference and confidence interval (CI) for the relation between the history of bone fracture and family economic status was -0.115 , which reflected the higher prevalence of bone fractures among women with the lower economic levels. About 25% out of all ORBFs were happened among 20% of the women with low economic status.Conclusion: It was concluded that economic status plays an important role in happening ORBFs among underprivileged women. A reorientation on women’s health care services in Iran with a focus on underprivileged postmenopausal women seems to be necessary. There is a need for inter-sectoral coalition between the policymakers of the health system and those of other organizations to reduce the economic inequalities among osteoporotic women. Considering the new emphasis on women’s health, as one of the Millennium Development Goals, as well as the significant improvements happened in its central indices in many countries, paying attention to the other new aspects of women’s health, such as social inequalities and equity and their distribution among different population groups is recommended.9 Even in generally wealthy Western countries, material deprivation and poverty are not uncommon.10 However, little knowledge exists about economic inequalities in fractures caused by osteoporosis. Moreover, investigating economic inequality among women with specific diseases is a new subject and the number of published studies conducted on such diseases, specifically, osteoporosis in developing countries is scarce. So, it can be claimed that the present study is a novel research on economic inequalities among the women with osteoporosis referring to a rheumatology clinic in Sanandaj, Iran. This rheumatology clinic was situated in one of the central streets of the city and it was assumed to be the only specific clinic for the rheumatic patients which could be available for all the patients with various economic statuses throughout the city. As a new approach in health inequality studies, in the present study, the family income index reported by the female osteoporotic patients was applied as a direct indicator to measure their economic status. Therefore, the aim of this study was to investigate economic inequalities among women with osteoporosis-related fractures in Sanandaj, Iran.The inequality in health has been recognized from centuries ago.In this cross-sectional study, convenient sampling was employed to recruit 220 women with osteoporosis referring to the only rheumatology clinic in Sanandaj from January to April 2013. Considering the non-probability sampling technique used in this study, during the data collection, all the osteoporotic patients referring to the abovementioned clinic were included in the study. The patients were diagnosed with osteoporosis by a rheumatology specialist physician based on DEXA method and Lunar DPX. Inclusion criteria for the study were postmenopausal women (50-75 years old) with T-score less than or equal to -2.5 which was measured at two points in their hip and spine. Exclusion criteria were postmenopausal women younger than 50 and women who did not agree to participate in the study. Twenty-five respondents did not meet the inclusion criteria and, thus, excluded from the study .All the respondents were interviewed face to face by an expert nurse in osteoporosis. The interviewer was not aware of the study hypotheses. To reduce the selection bias, all the patients referring to the clinic were included in the study if they have the inclusion criteria. To control the information bias (misclassification in covariates), it was tried to define the variables for participants, clearly. The interviewer was trained on the subject and was asked to apply the same method of data collection for all the participants.A series of questions and tools regarding socio-economic, demographic and anthropometric characteristics of the respondents including age (years), marital status (married/single or divorced/widowed), job (housekeeper/employed/retired), education status (illiterate/elementary/high school/diploma), history of fractures due to osteoporosis (yes/no), weight (kg), height (cm), body mass index (BMI) as well as family income  was designed. The weight and the height of the respondents were measured applying the digital scale model Beurer BG55 and the Stadiometer model Seca 222, respectively. All the measuring processes of BMI for all the patients were conducted by a rheumatologist in the clinic.11 suggested, monthly income is one of the main indicators for representing the economic status among populations. Chandola and Marmot12 also, recommended income, wealth and assets as good indicators of an individual’s situation in the labor market and his/her material standards of living. Despite these recommendations, there have been reported some limitations for this indicator including the possibility of measurement biases and other possible problems such as measurement error, missing data and non-responsiveness.12 In the health economics literature, proxies including consumption and assets indices have been proposed to overcome such possible problems.In this study, the self-reported family monthly income was considered as an indicator for the patients’ economic status. As Oakes and KaufmanIn the present study, we chose to use family monthly income as the only indicator for economic status of the respondents due to some limitations reported in “Limitation” section of this paper. However, in order to alleviate the above-mentioned possible problems, it was decided to collect data through interview in a private room. During interviews, the respondents were explained about the purpose of the study, the anonymity and the privacy of the data and, also, the fact that the question on monthly income was only for research objectives.Firstly, all the subjects were divided into 5 subgroups based on the range of their monthly income, and, secondly, 20% of the first group and 20% of the last group representing the lowest and the highest level of economic status, respectively, were selected.Concentration index decomposition (CID) is one of the most common methods for measuring inequality. The CID was made based on concentration curve (CC). This index along with its related CC provides a means for measuring the degree of income-related inequality in a specific health variable.13The concentration index (CI) was defined as twice the area between the CC and the line of equality (the 45 degree line running from the bottom-left corner to the top-right). The index takes a negative value when the curve, called as Lorenz curve (LC), lies above the line of equality, indicating disproportionate concentration of the health variable among the poor patients, and a positive value is when it lies below the line of equality. If the health variable is ‘bad,’ such as ill-health, a negative value of the CI means ill-health is higher among the poor patients.14 The Gini coefficient was used to measure inequality in the distribution of income. Decomposing this measure helped us to understand the determinants of inequality.15CI was used to analyze the distribution size of income and wealth which measures inequality and poverty among populations.Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between the variables and the history of osteoporosis-related bone fractures (ORBFs) adjusted for other covariates. Data analysis was conducted applying STATA 12.0 software for Windows.The total number of osteoporotic women examined for eligibility was 245. The socio-economic and underlying characteristics of the osteoporotic women are shown in 2) was 2.59  (adjusted for covariates) decreased the odds of ORBFs among the study participants, although the latter was not statistically significant.As there is shown in In univariate analysis, the fourth  and the fifth  quintiles of economic status were found to be significantly associated with the higher rates of ORBFs. Non-significant positive associations were found between the second  and the third  quintiles and ORBFs.P = 0.16), which reflects the higher prevalence of bone fractures among women with lower economic levels. Calculated decompositions to obtain the decomposition of explanatory variables for the history of ORBFs are presented in The CI for ORBFs was -0.115 . The negative value of the CI indicated that the ORBFs are, disproportionately, concentrated among women with lower economic status . Such a result may be common as many people with low economic status may have a lack of financial ability to procure medicines and food items. Moreover, most of these people have a lower literacy than those with higher financial ability. So, they may not have enough knowledge regarding the osteoporotic fracture preventive actions.17 who reported that the lower income may be a barrier to adhere with osteoporotic medication. In their study, lower income was the most significant barrier among all the barriers. Therefore, policy makers should consider medication expenditure as an important barrier for appropriate treatments, which calls for more attention of health practitioners.This finding is similar with those found by Shehadeh-Sheeny et al,18There are similar studies within which the focus is, only, on the magnitude of inequality in the ORBFs, and no one has studied the issue applying the CI decomposition approach. Okumus et al, reported that despite the moderate awareness of postmenopausal women about osteoporosis, their knowledge regarding osteoporosis risk factors and complications was poor. They concluded that having a better understanding of osteoporosis related health beliefs among women at risk may be influential, as it may play a significant role in influencing an individual’s osteoporosis preventive behaviors.19 in a study investigating bone mineral density (BMD) in two different socio-economic population groups found that the most of older people from the low economic group crossed the fracture threshold earlier than those from the high economic group. Moreover, in another study,20 there was a significant association between absolute poverty and age-adjusted prevalence of femoral neck osteoporosis and lumbar osteoporosis, which confirms the findings of the present study. On the other hand, Syddall et al,21 in England, found no relationship between economic indicators and broken bone rate. They suggested that fracture and osteoporosis may not have a strong direct social gradient. As a reason for this dissimilarity, it can be stated that their study was focused on searching for direct factors and, therefore, the indirect factors like the level of income was neglected.Similar with those found in the present study, del Rio Barquero et al,13 In this study, the economic status accounted for 95.7% of inequality in the ORBFs and furthermore, the other determinants including illiteracy and unemployment accounted for the remaining 4.4%. It is noteworthy that these socio-economic factors were strongly associated with the economic status. Such results showed the usefulness of decomposition approach, as it combines the monitoring of inequality and understanding its determinants.The decomposition method helps to quantify the contributions of the determinants to economic inequality in health.22 recently, conducted a systematic review on the associations between socio-economic status  and BMD as well as osteoporotic fracture among adults. They concluded the limited existence of good quality evidence for associations between social inequalities in BMD and fractures occurrence. Clarification of whether the ORBFs are socially patterned may inform health care policy makers to consider the issue from a new perspective and, also, may warrant the health care providers to consider the importance of such socio-economic characteristics while planning for health education and promotion programs.Brennan et al,23 conducting an ecological study and Leslie et al24 applying a case-control design concluded that the lower levels of income were associated with the higher rates of hip fracture among American and Canadian people, respectively. In another study, Johnell et al25 found an association between the lower levels of economic prosperity and the lower rates of hip fracture. Wang and Dixon26 and Piao et al16 conducted cross-sectional studies on women in the United States and Italy, respectively, and both concluded that the lower levels of education or income were associated with the lower levels of DXA bone mineral density.Although, as a result of the differences in the designations of the studies, the straight comparison between our findings and those found in the previous studies is difficult, it seems that the present findings are in line with the international literature within which the ORBFs are unequally distributed among societies. For instances, Zingmond et al13 They suggested several strategies such as identifying the demographic and economic characteristics of vulnerable and disadvantaged groups and targeting the subsidy plans from the rich to the poor.In current decades, CID has been considered as an approach to help policymakers in defining the main issues for their interventions to reduce socio-economic inequality in health. In the present study, there were positive contributions between age, marital and educational status with inequality. Considering the remarkable role of socio-economic inequality in the unequal distribution of bone fractures among Iranian women with osteoporosis, there is an urgent need for appropriate strategies aiming to address the determinants of osteoporosis-related preventive behaviors among the poor to decrease the prevalence of consequent fractures among underprivileged women. Also, as suggested by Morasae et al, policymakers and stakeholders should bring human health to the forefront of every other issue while designing their programs.In the present study, family monthly income was the only indicator for economic status of the respondents due to some limitations existed while data collection. The findings in the present paper are parts of a comprehensive study with a high number of variables. As the number of items in the original questionnaire was high, the researchers decided not to include the assets/consumptions indices and, instead, to be satisfied of the family monthly income as the only indicator to measure economic status of the respondents. For future research, it is suggested to use proxies like consumption or assets indices to measure economic status of the osteoporotic patients. Moreover, since the data collection conducted by face to face interview, there may be a risk for misclassification bias. Also, because of the nature of interview, there may be a risk for underreporting by the patients. For future research, it is suggested to calculate unbiased estimation by adjusted methods for misclassification . On the other hand, due to differential misclassification, the bias-adjusted ORs cannot be determined. As the most of osteoporotic patients refer to the abovementioned osteoporosis clinic, the generalizability of the findings sounds to be established.Moreover, due to the lack of a control group, there may be a potential for bias. It is suggested for future studies to consider the most important confounding factors such as differences in indices of bone density. In general, it is recommended that the sample size for health inequality studies to be larger, but in the present study it was not possible due to the low number of osteoporotic patients referred to the rheumatology clinic in Sanandaj and time limitations, as well.As the economic status play an important role in osteoporotic fractures occurrence among the poor women, a reorientation of women health care services in Iran focusing on underprivileged postmenopausal women seems to be necessary.Health policymakers and stakeholders should try to bridge the gap between the health promotion of the poor and the rich women with osteoporosis. Such a gap may results from inequalities in the social determinants of the disease. In order to address the prerequisites for this gap, there is an urgent need for inter-sectoral coalition between the policymakers of the health system and those of other organizations to reduce the socio-economic inequalities among osteoporotic patients.This research was supported by Islamic Azad University-Sanandaj Branch and Arak University of Medical Sciences. The authors thank all those patients participated in the study.Ethical approval was provided by Ethics Committee in Islamic Azad University, Sanandaj Branch. Informed consent form was completed and signed by all the respondents.The authors have declared no conflict of interest.RM was involved in the conception of the study, performed the analyses and drafted the manuscript. NM and MHK were involved in the conception of the study, interpreted the results from the analyses, and HN assisted in drafting and revising the manuscript.


Telemedicine applications have been increasing due to the development of new computer science technologies and of more advanced telemedical devices. Various types of telerehabilitation treatments and their relative intensities and duration have been reported.The objective of this review is to provide a detailed overview of the rehabilitation techniques for remote sites (telerehabilitation) and their fields of application, with analysis of the benefits and the drawbacks related to use. We discuss future applications of telerehabilitation techniques with an emphasis on the development of high-tech devices, and on which new tools and applications can be used in the future.We retrieved relevant information and data on telerehabilitation from books, articles and online materials using the Medical Subject Headings (MeSH) “telerehabilitation,” “telemedicine,” and “rehabilitation,” as well as “disabling pathologies.”Telerehabilitation can be considered as a branch of telemedicine. Although this field is considerably new, its use has rapidly grown in developed countries. In general, telerehabilitation reduces the costs of both health care providers and patients compared with traditional inpatient or person-to-person rehabilitation. Furthermore, patients who live in remote places, where traditional rehabilitation services may not be easily accessible, can benefit from this technology. However, certain disadvantages of telerehabilitation, including skepticism on the part of patients due to remote interaction with their physicians or rehabilitators, should not be underestimated.This review evaluated different application fields of telerehabilitation, highlighting its benefits and drawbacks. This study may be a starting point for improving approaches and devices for telerehabilitation. In this context, patients’ feedback may be important to adapt rehabilitation techniques and approaches to their needs, which would subsequently help to improve the quality of rehabilitation in the future. The need for proper training and education of people involved in this new and emerging form of intervention for more effective treatment can’t be overstated. In the last few years, telemedicine applications have been increasing due to the development of new computer science technologies and of more advanced telemedical devices. Long-distance communication can be easily achieved by videoconferencing, email, and texting, to name a few. Today there is the possibility of controlling robots, robotic arms, or drones at a distance. Thanks to these advancements, the course of human action has been considerably transformed . During Telerehabilitation has been developed to take care of inpatients, transferring them home after the acute phase of a disease to reduce patient hospitalization times and costs to both patients and health care providers. Telerehabilitation allows for treatment of the acute phase of diseases by substituting the traditional face-to-face approach in the patient-rehabilitator interaction . FinallyControlled studies on rehabilitation have demonstrated that quick management of an injury or a disease is critical to achieve satisfactory results in terms of increasing a patient’s self-efficacy. Hence, a rehabilitation program should start as soon as possible, be as intensive as possible, be prolonged, and continue during the recovery phase. A major factor is the initiation time, which, in general, should begin as soon as possible. In most cases, the initial stages of rehabilitation, after the occurrence of a disease or injury, could be performed by patients at home even if they need accurate and intensive treatment. For these reasons, telerehabilitation was developed to achieve the same results as would be achieved by the normal rehabilitation process at a hospital or face to face with a physiotherapist. Various types of telerehabilitation treatments and their relative intensities and duration have been reported .The first scientific publication on telerehabilitation is dated 1998 and, in the last few years, the number of articles on the topic has increased, probably because of the emerging needs of people and due to the development of exciting new communication and computer technologies. A remarkable increase in the number of patients treated by telerehabilitation is noticeable from 2002 to 2004. After a subsequent decrease, the number of patients assisted by telerehabilitation increased starting from 2007, probably due to the support of new technologies and the overcoming of the initial skepticism to which every new technology is subjected.Telerehabilitation is primarily applied to physiotherapy ,7, and nBritish Medical Journal, Oxford Journals, Biomed Central, and CINAHL using the Medical Subject Headings (MeSH) “telerehabilitation,” “telemedicine,” and “rehabilitation,” as well as “disabling pathologies” . Parameters applied were English language, at least one keyword corresponding to the search terms in the title or abstract, and study based on the evaluation of clinical trials. An additional evaluation criterion was the publication of articles in peer-reviewed journals. The search was carried out in 2016 for the years January 1996 to January 2016. Moreover, we selected and examined 45 books and other online materials through Google search, university of Camerino E-database, and the central library of University of Camerino. We retrieved more than 400 articles on telerehabilitation or related topics. A further analysis performed by 2 researchers independently reading article titles and abstracts reduced the results to less than the 25% of articles.We systematically searched the literature in the PubMed and Medline databases, We excluded studies or other materials published before 1996 from our analysis. This is because, as We evaluated the relevant articles with the standard criteria of the Newcastle-Ottawa Scale for assessing the quality of nonrandomized studies in meta-analyses . OverallThe literature search identified 488 abstracts, 127 of which we analyzed in detail. Among these 127 articles, we excluded 100 in a full-text analysis  saving time and money, and avoiding unnecessary travel and discomfort to the patient. The disadvantages are also common among different telerehabilitation systems. These include limited flexibility in the use of the various medical devices appropriate to patients’ differing needs.In the case of neurological diseases such as brain injury or cognitive problems, the best rehabilitation for patients is to stimulate the brain with adequate environmental interactions. Probably due to the short history of neurological rehabilitation techniques, neurological telerehabilitation approaches are not clearly defined at this point and have no concrete theoretical bases . Recent The first conference on virtual reality applied to medicine was the Medicine Meets Virtual Reality conference . AdvantaHealth care treatment closer to the needs of the specific pathologies of the patient improves the quality of life and often decreases the duration of treatment. It has been shown that virtual reality can be used for the assessment and rehabilitation of specific disabilities resulting from brain injury, executive dysfunction, memory impairments, spatial disability, attention deficits, and unilateral visual neglect. A virtual urban environment for the treatment of 27 patients with moderate and severe brain injuries was developed in which patients needed to navigate in the simulator. However, this study showed no improvement due to the number of repetitions .Another example of a telerehabilitation system is the Rehab@Home framework used to perform rehabilitation in the domestic setting for stroke patients . The fraA telerehabilitation system was applied to 99 poststroke patients to evaluate their quality of life. The authors observed a statistically significant change in both interventions . Actually, both modalities were effective in improving quality of life and depression outcomes for participants at less than 6 months after their stroke. The goal of this study was to obtain better results for robotic rehabilitation, but the findings obtained did not show significant differences between the 2 groups .A telerehabilitation project called H-CAD was developed from 2003 to 2005. H-CAD is a system for patients with multiple sclerosis, stroke, or traumatic brain injury for performing upper limb rehabilitation treatment, at home. A help desk was developed to guide the patients in developing a proper exercise regimen by evaluating the performance periodically. Patients had the possibility to interact with doctors at the hospital through a teleconferencing system. The process was carried out in 2 test phases. The first phase was to test the results of the system with volunteers inside a hospital. The second phase was to test the system at home with ad hoc patients. The results were encouraging, and the doctors observed a marked improvement in patients using this system [More recently, the use of a telerehabilitation approach in the management of patients with depression was studied . Here, tMusculoskeletal disorders have a high impact on health care provision. A controlled study was conducted to assess the effectiveness of a telerehabilitation approach instead of standard face-to-face practice. A literature review analyzed 898 studies on the validity and reliability of Internet-based physiotherapy assessment for musculoskeletal disorders. Most of the telerehabilitation approaches were valid if they were applied for some physical diseases, except for lumbar spine posture, where the final score was not conclusive. In fact, results showed that the intervention had effectiveness scores from low to moderate .Another study demonstrated the use of Microsoft Kinect, a motion-sensing input device, to detect patients’ posture and movement, and it enabled caregivers to develop custom exercise patterns for each patient. Tests confirmed that the intervention had several benefits, particularly in creating a customized physical exercise program for physical rehabilitation .The application of telemedicine to cardiology, neurology, and rehabilitation is growing fast. For instance, its use in neurology in emergency departments is particularly critical because so many of them do not have a full-time neurologist. In 2016 it was reported that about 125,000 patients who had a stroke or symptoms of stroke used telemedicine-based technology in one form or another during treatment or rehabilitation. Telerehabilitation is a young field of telemedicine , and it Like every technology, telerehabilitation has some advantages and disadvantages. In terms of advantages, home telerehabilitation systems are cost effective if the intervention is just used to monitor or evaluate patients during corrective therapy ,29. The This review evaluated different application fields of telerehabilitation, highlighting its benefits and drawbacks. In conclusion, this analysis has shown that telerehabilitation is a new and interesting field but, unfortunately at present, there are no standard procedures or protocols, and different telerehabilitation facilities are being used for pilot studies only. Herein, we suggest the need for further research to improve the electronic equipment and devices, and to make their application as flexible as possible. This approach should significantly increase the reliability and effectiveness of telerehabilitation equipment to treat specific patient problems. Furthermore, in this context, feedback from patients may be important to update rehabilitation techniques to improve the quality of the rehabilitation itself. On the other hand, an important aspect of the future success of telerehabilitation involves proper training of people involved in these new forms of intervention, which may lead to more effective rehabilitation.


This study identifies the capabilities needed by small-scale fishers to participate in Fishery Improvement Projects (FIPs) for yellowfin tuna in the Philippines. The current literature provides little empirical evidence on how different models, or types of FIPs, influence the participation of fishers in their programs and the degree which FIPs are able to foster improvements in fishing practices. To address this literature gap, two different FIPs are empirically analysed, each with different approaches for fostering improvement. The first is the non-governmental organisation-led Partnership Programme Towards Sustainable Tuna, which adopts a bottom-up or development oriented FIP model. The second is the private-led Artesmar FIP, which adopts a top-down or market-oriented FIP approach. The data were obtained from 350 fishers surveyed and were analysed using two separate models run in succession, taking into consideration full, partial, and non-participation in the two FIPs. The results demonstrate that different types of capabilities are required in order to participate in different FIP models. Individual firm capabilities are more important for fishers participation in market-oriented FIPs, which use direct economic incentives to encourage improvements in fisher practices. Collective capabilities are more important for fishers to participate in development-oriented FIPs, which drive improvement by supporting fishers, fisher associations, and governments to move towards market requirements. The sustainability of fisheries is driven in large part by the alignment of fisher practices with management goals , 2. StatThe most dominant private incentive mechanisms for sustainable fisheries is the Marine Stewardship Council (MSC) standards, against which fisheries practices, the health of stocks and habitats, and the capacity of management to deliver sustainable outcomes are measured and certified . Howevernotional condition ).The PPTST FIP targets a very wide range of fishers across the six municipalities of Sablayan, Mamburao, Paluan, Sta. Cruz, Calintaan, and Rizal, Occidental Mindoro see . FishersThis study analyses fishers’ decisions to participate in the two FIPs . The firTesting the participation choices requires identifying significant variables that affect income and risks of fishers. The literature on decision making has extensively described the characteristics of decision makers that affect their level of income and risk e.g. –36). For. For36])Capabilities are defined as the specific skills, practices, and forms of social organisations required to deliver certain tasks in pursuit of long-term goals , 21. TheCasas–local elites or patrons who control trade and provide credit for fishing, as well as for household needs such as education and health . Bas. BasCasaThe individual risk attitude and socio-demographic variables influence the required income and acceptable risk for the decision maker , 35. ThiCasas is either improving or limiting the participation of fishers. These collective capabilities reduce the exposure of fishers to risks by acquiring parts of investments to external actors and developing fishers’ capabilities through bottom-up comprehensive FIPs, and thus improve their income. We assume that membership to a fisher association strengthens the social relationships among fishers, enables fishers to improve the management of their fisheries, and allows access to the external resources that help fishers to improve their fishing activities in order to comply with FIP requirements )β’ represents the coefficient of outcome explanatory variables x, γ is the selectivity bias, λ is the inverse Mills ratio, and ε is the random error term for the ordered probit equation. The y = j corresponds to the exact stage of participation in non-Artesmar, and is decomposed as follows: 1(y = 1) for non-participation, 2 for partial participation in the PPTST FIP, and 3 for full participation in the PPTST FIP. The variables in The y* represents a shadow variable ruling the ordered stages of participation to which non-Artesmar fishers belong: Before running the probit and the ordered probit models, two steps were conducted. First, all independent variables were checked for multicollinearity using the Variance Inflation Factor (VIF), which in this case gave values well below 10 for all explanatory variables see , implyinFinally we added two extra steps to the model to test the robustness of our result, as shown in the supplementary information see  Tables. First the modelling results will be presented for the first stage decision on participation in the Artesmar FIP, followed by the results for the second stage decision on participation in the PPTST FIP and the ordered outcome of non-participation in FIP, partial and full-participation in PPTST FIP.2 = 0.00, which implies a good model fit at α = 0.01. Consistent with our hypothesis, the initial investment for fishing boats, risk attitude, and number of family members are significant and positively contribute to the fishers’ choice to participate in the Artesmar FIP. Increasing initial investment for fishing boat reflects higher capabilities of fishers in terms of boat size, boat engine, and fishing equipment. These capabilities enable fishers to deliver tuna in the chain, therefore increasing their likelihood of choosing the Artesmar FIP and their chances of gaining higher income to recover their investments. A higher value for risk attitude of fishers as manifested by fishers preference to sell through quality buying, increases the likelihood of fishers to participate in the Artesmar FIP. A higher number of family members indicates that fishers also have an increase likelihood to participate in the Artesmar FIP. Based on field observations and interviews, fishers participating in Artesmar FIP often operate as part of a large scale family business. As shown in the literature [The results presented in terature , family Contrary to what was expected, the type of fishing employment has a negative effect on participation in the Artesmar FIP. The results show that the more fishers operate part-time or target species aside from tuna, the more likely it is that they will participate in the Artesmar FIP. Most part-time tuna fishers shift from tuna fishing to catching other species during the low season for tuna catches in order to recover their costs of operation. Moreover, based on field interviews, some fishers believe that tuna stocks are declining over time, and therefore search for alternative catch to balance the risks of going out to sea.The results of the ordered probit model on the degree of participation of fishers in the PPTST FIP are presented in The membership to a fisher association also increases the likelihood of fishers to move from non-participation to full-participation in PPTST FIP. Based on interviews, fishers in the PPTST FIP perceive that joining a fisher association will help them improve the quality of their tuna, and will finally lead to higher tuna prices. The fisher association increases the perceived benefits of fishers since the association helps fishers to generate funding and subsidy such as fishing aids from the government, which improves their fishing activities. Moreover, a fisher association also organises activities such as the marine guards to prevent illegal fishing and conservation activities as part of the improvement process in the FIP. Finally, the risk attitude of fishers shows a positive effect in terms of pushing fishers to fully participate in the PPTST FIP. This means that fishers are willing to sell more through quality buying because these fishers are confident that they acquired the knowledge and skills to improve the quality of tuna catches, which in turn increases the probability of getting higher prices for the fish they land.Having alternative sources of income has a negative and significant effect on the participation of fishers in the PPTST FIP as compared to those fishers who solely rely on fishing as a source of income. Based on interviews, and consistent with literature related to fishing as a form of employment (e.g ), some fFinally, the significant variables in the ordered probit model are further analysed by deriving their marginal effects, which show the change in probability when an independent variable increases by one unit. Calculating marginal effects in the second stage decision shows both the patterns and requirements for fishers to move from one participation stage to another. Aside from the direct interpretation of the marginal effects, the graph also shows the trends of marginal effects in selecting for partial or full participation in the PPTST FIP. The five variables show an increasing trend, which means that they generally enhance the participation of fishers from non- to full-participation in the PPTST FIP. The variables membership to a fisher association and risk attitude are highly significant in non, partial, and full-participation in PPTST FIP at α = 0.01. This means that both variables are highly important in improving the participation of fishers in the PPTST FIP. The type of fishing employment, operating distance, and financing operation are significant at α = 0.05 and at 0.10. It is also notable that among the five variables, the membership to a fisher association shows the highest marginal values, making it highly important for both partial and full participation. The majority of the partial participants are able to get funding from the government to improve their livelihoods through a fisher association. Full participants also benefit by being members of a fisher association by having regulatory support to fight IUU fishing in their area, thus ensuring greater legality of fish caught and traded.Based on these results we now further elaborate on how the capabilities of fishers influences fisher decision making for different levels of participation in top-down and bottom-up comprehensive FIPs, and on the influence these factors have on the design of different FIPs as a means of reaching goals of improved fishery practices and fisheries management.The results show that different types of capabilities influence the decision of fishers to join different kinds of FIPs. First, individual firm capabilities, such as initial investment and type of fishing employment, increase the likelihood for fisher participation in response to market-oriented FIPs, which provide economic incentives through dock side transactions based on quality. These individual firm capabilities are more likely to be exhibited by those with considerable financial capacity, owning and financing several fishing boats. Moreover, these fishers are also more likely to be engaged in other chain-related activities. However, consistent with now wider observations of how economic decisions are embedded in wider social or community relations , 66, theCasas . Howevesas , top doSecond, the results indicate that the design of FIPs also influences the delivery of incentives to fishers, which also affects inclusiveness and overall impact. As argued above, top-down FIPs appear to be better able to deliver more transparent price signals to fishers. The case of the Artesmar FIP shows that companies like Meliomar invest in vertical coordination and in doing so control the chain from production to export. They are thus better able to set higher prices for higher quality fish and to transmit this price incentive to fishers , 75. On Finally, these results open up questions around the degree of complementarity and competition that might exist between FIP models in relation to inclusion and improvement. While the results point to the differences between top-down or bottom-up comprehensive FIPs, it may not necessarily be the case that these or other FIP models are opposed or in competition. Instead, building on nascent ideas of FIP design , two FIPOur results indicate the overall importance of considering fisher capabilities in understanding decisions of fishers to participate in different kinds of FIPs. The individual firm capabilities stimulate fishers to participate in strongly market oriented top-down FIPs while collective capabilities enable fishers to improve their practices and to participate in bottom-up FIPs aimed at wider fishery and community development goals. These types of capabilities and FIP models have consequences for the inclusiveness of different fishers, for which three insights are generated in this study. First, the top-down FIPs appear to be more exclusive, given that there are a few numbers of fishers who have the capabilities and lower risk aversion to comply with its requirements. Second, bottom-up FIPs appear to be more inclusive, aiming to provide broad support to the development of fisher capabilities and the institutional support provided to them to improve their practices on the water. Third, the two FIP models exhibit competing inclusion when implemented in the same fishery, yet also exhibit potential complementarity in terms of delivering incentives and improving governance of the fishery.We also conclude that in order to increase the participation of fishers, those designing FIPs need to not only recognize the economic utility that a fisher could derive from participation, but also to identify and build fishers capabilities to participate in a FIP. Moreover, FIPs must also balance both the deliverance of incentives to individual fishers and the improvement in the governance of the fishery in order to enhance participation of fishers and thus achieve high sustainability impact. Future research may elaborate on the implementation of FIPs to poor and well performing fishers and to different fisheries (e.g. tuna or other species), and on their consequences to the inclusiveness and fishery improvement. Finally, focusing on ways to enhance the participation of fishers in FIPs and in other private incentive mechanisms is also relevant to achieve higher sustainability outcomes.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.


Sirenomelia and anencephaly are well-defined congenital malformations that usually occur independently.We report a case of combined sirenomelia, anencephaly and complete rachischisis, diagnosed in the 16th week of gestation.To our knowledge, this is the 7th case in the literature and the first that is diagnosed so early in pregnancy.The final diagnosis is confirmed with radiological examination after the termination of pregnancy.Prenatal diagnosis of sirenomelia is difficult due to the presence of kidney agenesis and severe oligohydramnios.The combination of sirenomelia and craniorachischisis totalis is extremely rare and prenatal ultrasound scan are a challenge, even for experts in the field. It presents with a variety of phenotypes and is incompatible with life, while death usually occurs in the perinatal period.,3 The incidence of sirenomelia varies between 1.1 and 4.2 per 100,000 births and has no difference among ethnic groups. It is diagnosed by prenatal ultrasonography, while antenatal ultrasonography scan findings include oligohydramnios, renal agenesis, and a fibula between the tibiae.Sirenomelia sequence, also known as sirenomelia, is a birth defect of the lower body, characterized by apparent fusion of the legs into a single lower limb.Anencephaly is characterized by an open neural tube in the cephalic region, with an exposed mass of degenerating neural tissue on the skull floor. The cranial vault is absent, producing characteristic bulging of the eyes and absence of the neck. It is presented with a gross malformation in both the membranous neurocranium and chondrocranium. Anencephaly is classified as meroacrania if the defect does not affect the foramen magnum, holoacrania if it extends through the foramen magnum, and holoacrania with rachischisis if it presents with spina bifida.The coexistence of sirenomelia with anencephaly and rachischisis totalis is a very rare condition and there have been only 6 cases reported in the literature so far.2A 20-year-old woman with an uncomplicated previous pregnancy and an unremarkable medical and family history was first seen at 25 weeks of her second gestation. During ultrasound scan, severe oligohydramnios and growth restriction were noted and she was referred to our department for investigation and management of the pregnancy.Ultrasonography demonstrated anencephaly Fig.  and spinInternal examination showed the absence of the rectum and both kidneys, ureters, bladder, and urethra. The diagnosis of anencephaly and symelia apus was done both with external examination and radiological examination of the fetus.3 In 1991, Rodriguez et al, described a case of sirenomelia combined with anencephaly, on a monozygotic twin. Ultrasound scan at 25 weeks of gestation demonstrated 1 normal twin and 1 with alteration of the head and abnormal lower limbs. The twins were delivered at 32 weeks of gestation. The first twin was a female who underwent laparotomy and right adnexectomy right after birth due to a large adnexal cyst that proved to be a mature cystic teratoma with granulomatous reaction against squamous epithelial cells in the wall of the cyst. An autopsy report showed a duplication of the cervix, uterus, and vagina and a normal left ovary. The second twin was a hydropic stillborn anencephalic sireniform fetus of unidentifiable sex. External examination showed the absence of cranial vault, bulging eyes, cleft palate, flat nose, low set and malformed ears, along with a short neck.Sirenomelia with anencephaly was first reported in 1953 by Battaglia and Fraccaro.In our case reported, the patient had a singleton pregnancy that was diagnosed at her first visit for an ultrasound scan at 25 weeks of gestation. The ultrasound showed severe oligohydramnios and intrauterine growth restriction (IUGR). Upper limbs appeared to be normal while only 1 femoral bone was recognized. Our presented case combines cephalic and caudal defects of the embryo and could be considered an example of the “axial mesodermal dysplasia spectrum.”The originality of this case lies on the fact that during the first prenatal visit, in spite of severe oligohydramnios, we were able to identify via sonography in the early second trimester of pregnancy, findings that constituted with anencephaly and sirenomelia. Although our case was a singleton pregnancy, sirenomelia combined with anencephaly seem to be in excess frequency in monozygotic twins.Anencephaly in patients with sirenomelia could be the only neural tube defect (NTD) or it could be associated with an exposed area of spinal cord of variable extent. The extent of the NTD could be inversely correlated with the lower limb abnormalities. In our case, the patient had oligohydramnios, which made the prenatal diagnosis a difficult process. However, based on the ultrasound findings of severe IUGR, single femoral bone, and anencephaly, the pregnancy was terminated and the diagnosis was confirmed by observational and radiologic studies of the fetus. Ultrasonographic diagnosis of anencephaly could be easy but the combination of anencephaly and oligohydramnios should set the suspicion for more complex anomalies. Prenatal diagnosis of sirenomelia is difficult due to the presence of kidney agenesis and severe oligohydramnios. The final diagnosis is confirmed with radiological examination after the termination of pregnancy.Polyhydramnios is found frequently in gestations of anencephalic infants while oligohydramnios is observed mostly in sirenomelia.4Sirenomelia with anencephaly and rachischisis totalis is a rare complication of pregnancy. This anomaly is not compatible with life and the diagnosis is extremely challenging, thus highlighting the importance of a thorough ultrasound examination. Termination of pregnancy is recommended upon diagnosis, with a detailed consultation followed by close-up monitoring for future pregnancies.


In the Democratic Republic of Congo, the penal code prohibits the provision of abortion. In practice, however, it is widely accepted that the procedure can be performed to save the life of a pregnant woman. Although abortion is highly restricted, anecdotal evidence indicates that women often resort to clandestine abortions, many of which are unsafe. However, to date, there are no official statistics or reliable data to support this assertion.Our study provides the first estimates of the incidence of abortion and unintended pregnancy in Kinshasa.We applied the Abortion Incidence Complications Method (AICM) to estimate the incidence of abortion and unintended pregnancy. We used data from a Health Facilities Survey and a Prospective Morbidity Survey to determine the annual number of women treated for abortion complications at health facilities. We also employed data from a Health Professionals Survey to calculate a multiplier representing the number of abortions for every induced abortion complication treated in a health facility.In 2016, an estimated 37,865 women obtained treatment for induced abortion complications in health facilities in Kinshasa. For every woman treated in a facility, almost four times as many abortions occurred. In total, an estimated 146,713 abortions were performed, yielding an abortion rate of 56 per 1,000 women aged 15–49. Furthermore, more than 343,000 unintended pregnancies occurred, resulting in an unintended pregnancy rate of 147 per 1,000 women aged 15–49.Increasing contraceptive uptake can reduce the number of women who experience unintended pregnancies, and as a consequence, result in fewer women obtaining unsafe abortions, suffering abortion complications, and dying needlessly from unsafe abortion. Increasing access to safe abortion and improving post-abortion care are other measures that can be implemented to reduce unsafe abortion and/or its negative consequences, including maternal mortality. The Democratic Republic of Congo (DRC) is slowly emerging from decades of armed conflict that has stunted national development and produced disastrous consequences for the health of its citizenry. The country is beginning to rebuild its infrastructure, including its health system, and effort is being made to improve sexual and reproductive health indicators –3. UntilSurveys conducted in the 1990s and early 2000s provide evidence that women in Kinshasa frequently resorted to abortion in the past: at least 15% of ever-pregnant women admitted to having had at least one abortion in their lifetime , 8. SeveThe DRC’s penal code prohibits the provision of abortion altogether , 14. In Our study draws on multiple data sources to estimate measures of abortion incidence and unintended pregnancy. The authors conducted three surveys to collect the primary data used in this study: Health Facilities Survey (HFS), Health Professionals Survey (HPS), and Prospective Morbidity Survey (PMS). The HFS and PMS provide information on the annual number of women treated for abortion complications (i.e. received postabortion care (PAC)) at health facilities across Kinshasa while the HPS generates information that is used to calculate a multiplier representing the number of women who have abortions for every woman who has an induced abortion and receives facility-based treatment. To derive our estimates of induced abortions and unintended pregnancies, we also draw on other data sources, including official government statistics and the 2013–2014 Democratic Republic of the Congo Demographic and Health Survey (DRC DHS), for Kinshasa-specific population and poverty estimates, age-specific fertility rates, and the proportion of women who deliver in health facilities , 22. We The study team compiled a list of 2,713 health facilities in Kinshasa whose level of equipment and staffing make them likely to provide PAC. Although the Ministry of Health possesses an official list of registered health facilities, many facilities in Kinshasa are not registered with the government. Thus, the study team combined the Ministry of Health’s official list with two listings conducted for other research projects that members of the study team have been involved in. After combining the three lists, we removed all duplicate facilities that appeared on the combined list. The compiled list included information on level of facility and ownership type ). In the public sector, four levels of facilities are capable of treating abortion complications: university hospital, provincial hospital, general reference hospital/reference health centers, and health centers. In the private/NGO sector, two levels of facilities exist: hospitals and health centers. We removed all specialist facilities that would not be expected to provide PAC such as pediatric, dental, and eye clinics.To obtain a representative sample of facilities for Kinshasa, we used stratified random sampling to select 423 facilities. We first split the facilities by their designated levels  and then stratified by ownership type . We collapsed private and NGO facilities into the same category due to difficulties in distinguishing between the two types. Since we expected hospitals to provide a large proportion of postabortion care and they are generally smaller in number, we included 100% of hospitals in our sample. Given that health centers typically do less PAC and they are usually large in number, we normally select a small fraction of them for inclusion in the sample, the larger the total number the smaller the proportion. We initially planned to include 10% of health centers, regardless of ownership type, in our sample, but due to the low number of public health centers, we opted to oversample facilities in this facility type. Thus, we randomly selected 19% of the public health centers and 10% of the private and NGO health centers.In each of the facilities in our sample, a senior staff member who would be knowledgeable about the facility’s PAC services was interviewed after obtaining his/her consent to participate in the survey. In larger facilities, such as hospitals, the chief of the obstetrics and gynecology department or an obstetrician-gynecologist was usually selected. In smaller facilities, such as health centers, this person was typically the director or another provider (e.g. nurse or midwife). Each consenting staff member completed a face-to-face interview using a structured questionnaire. The respondent was asked if the health facility treated complications from abortion, either spontaneous or induced, that were serious enough to require treatment in a health facility. If the respondent reported that the facility provided this service, the interviewer asked for the number of women treated for abortion complications as outpatients and as inpatients in an average month and in the past month. If the respondent was unable to provide these numbers, he or she was asked to provide the number of women treated in the average year and past year. We requested estimates for two time frames to capture variability that might exist in monthly or yearly caseloads, as abortion, especially induced abortion may be seasonal in some contexts , 24. ForFieldwork for the HFS was conducted in April and May 2016. The survey team successfully conducted interviews at 361 out of 423 facilities in our sample, resulting in an overall response rate of 85% . ResponsThe study team conducted the Prospective Morbidity Survey (PMS) after HFS data collection was completed. All facilities that reported providing PAC in the HFS were eligible to participate in the PMS. The PMS consisted of two parts, patient survey and provider survey. The type of information collected differed by type of survey. While the patient survey collected information on the characteristics of women obtaining PAC and the conditions under which abortions take place, the provider survey focused on the severity and management of abortion complications. The study team invited each of the eligible health centers to send one staff member and each of the hospitals two staff members to participate in a three-day interviewer training. Clinic staff were recruited to serve as interviewers in their respective facilities because they were in a position to know when PAC patients were being treated and to be able to determine the appropriate time to conduct interviews with consenting respondents and their primary care providers.Interviewers attempted to conduct interviews with all women treated for abortion complications, spontaneous or induced, over a 30-day period. All women, regardless of whether they were treated as inpatients or outpatients, were eligible to be included in the study. Interviewers approached patients once they were in stable condition and sought informed consent to conduct the interview. If an interviewer was the patient’s primary care provider, he or she was not permitted to interview the patient and had to ask another interviewer working in the facility (if there was one) or ask his or her supervisor to conduct the interview. The study team restricted interviewers from interviewing their patients to reduce any concern that patients might feel about their responses affecting their treatment. After the interview, the interviewer asked the respondent for her consent to interview the patient’s health provider. If the patient gave her consent, then the interviewer approached the patient’s provider to obtain informed consent and carry out the interview.For various reasons, not all eligible patients were interviewed in the PMS. Interviewers filled out a tracking sheet that kept track of missed cases and the primary reason they were missed. Reasons for missed cases included: refusal to participate; interviewer not present at the facility when the respondent was there; interviewer was the patient’s primary care provider and another interviewer or supervisor was unavailable; patient transferred to another facility for further treatment; too sick to participate; or died. By keeping track of missed cases, we determined the total number of women treated for abortion complications during the 30-day study period, regardless of whether they were interviewed. For each health facility, we determined the facility’s PAC caseload during a 30-day period by adding the number of women interviewed to the number of missed cases. However, not all women who obtain PAC in health facilities across Kinshasa necessarily need treatment, particularly those who induced their abortions using misoprostol. Though HFS respondents were instructed not to include abortion complications that would have been resolved on their own (without any care) in their counts of PAC patients, these instructions were not given in the PMS. Thus, the PMS possibly collected data from women whose abortion complications did not necessarily need treatment. To make the PMS caseload consistent with the caseload captured in the HFS, we subtracted women who likely did not need treatment. According to the data collected in the PMS, at least 5% of PAC patients had misoprostol-induced abortions, experienced no complications, and were discharged in good health in less than 24 hours. We assumed that these women were in the process of completing their abortions and would not have needed PAC. We subtracted these women from the total number of PAC cases treated in health facilities. Similar to estimates produced using the HFS, we multiplied the 30-day caseload by 12 to determine the annual caseload for each health facility.Among the 262 facilities eligible to participate in the PMS, 223 participated, resulting in a response rate of 85%. Refusal to participate was the most common reason for non-response; during the period between the HFS and PMS, four facilities eligible for the PMS closed down. Fieldwork for the PMS took place in July and August 2016.The study team compiled a list of professionals who are knowledgeable about the conditions of abortion provision and post-abortion care in Kinshasa. This list, which was compiled in consultation with colleagues working in different domains of reproductive health, including research, policy, and community health programs, consisted of medical doctors, nurses, researchers, policymakers, advocates, social workers, NGO staff, and other individuals who would be well-informed about women’s behaviors and outcomes in seeking and obtaining abortion. Approximately two in five respondents were clinicians  and the rest were non-clinicians.The primary purpose of the Health Professionals Survey was to collect information on: 1) distribution of abortions by method used  2) distribution of women having abortions by type of method used and by type of provider  3) proportion of women experiencing complications  by type of method used and by type of provider and 4) proportion of women experiencing complications who are likely to obtain care at a health facility by type of method used. Because women’s access to abortion, particularly provider types and methods of abortion, likely varies by women’s socioeconomic status, respondents were asked to provide responses separately for poor women and non-poor women. In total, interviews were conducted with 115 respondents. Data from two respondents were not analyzed because they did not provide responses to any of the key questions. Fieldwork for the HPS was conducted from May to August 2016.Several steps were taken to estimate the incidence of abortion and unintended pregnancy in Kinshasa.We used data collected in the HFS and PMS to estimate the PAC (induced or spontaneous) caseload in health facilities across Kinshasa. Though the HFS collected data on PAC caseloads for the past month/year and average month/year, we chose not to use the past month/year estimate because it was considerably lower than both the average month/year estimate and the PAC caseload estimated from the PMS, which was based on prospective reporting over a period of one month. In the case of HFS estimates for the average month, respondents report retrospectively and provide an average monthly caseload based on their experience. The PMS estimate was slightly higher than the HFS average year estimate. One possible explanation is that PAC caseloads were underestimated in the HFS. HFS respondents were asked to rely on their memory when reporting PAC caseloads for the average month or average year. Consequently, recall bias may have affected estimates. The PMS, in contrast, does not suffer from the effects of recall bias because interviewers attempted to conduct interviews with all women treated for abortion complications prospectively as they were admitted for treatment, over a 30-day period. Even if all eligible women were not interviewed, interviewers kept track of the number of missed cases and reported them to the survey team at the end of the observation period. Alternatively, PAC caseloads could have been overestimated in the PMS. Health facility workers, who served as interviewers, were financially remunerated for each pair of patient and provider interviews conducted during the study period. It is, therefore, possible that some interviewers fabricated cases to receive the incentive. While this cannot be ruled out, we expect it to be minimal because supervisors were instructed to verify the existence of each case.If a health facility participated in both the HFS and PMS, we averaged the two data points to obtain an average caseload for that facility. Otherwise, we used the caseload for the average year as the average caseload for that facility. In total, 35 health facilities did not participate in the PMS.Some women who received PAC in a heath facility were referred to another facility, usually a higher-level facility, for additional care. As a result, these women would have sought treatment in two facilities, and would be double-counted in estimates of PAC provision. HFS respondents were asked to estimate the number of women who received PAC in their facility and then referred to another facility for additional treatment in the past month or year. If the number of referrals were given for the past month, we multiplied this number by 12 to produce an estimate for the past year. Across all facilities in Kinshasa, we calculated that 5,606 referrals were made in the past year. Dividing the number of referrals by the total number of post-abortion cases  treated in the past year, we determined that 17.2% of all PAC cases were referred to another facility. Not all women referred to another facility necessarily seek treatment, but because no data exists on the percentage of women referred for PAC who seek treatment, we assumed that the percentage seeking treatment is similar to the percentage of women in Kinshasa delivering in health facilities, which according to the most recent DRC DHS is 98% . By multThe objective of this study is to estimate the incidence of abortion in Kinshasa. Given that Kinshasa has a high density of health facilities, women from nearby areas may come to Kinshasa for PAC. Not taking this into account would overestimate the incidence of abortion. According to data collected in the PMS, 3% of women receiving PAC in health facilities in Kinshasa live outside the city. Thus, we subtracted 3% of PAC cases from the total number of abortion complications treated in health facilities in Kinshasa.To determine the number of complications that are due to induced abortions, we subtracted the number of complications resulting from spontaneous abortions from the total number of PAC cases. Similar to previous studies applying the AICM , 19, 25,Not all women who experience a late miscarriage seek treatment at health facilities. Similar to previous studies where the AICM has been applied , 20, 28,We used data collected in the HPS to determine the proportion of women having induced abortions who receive PAC. The HPS provided estimates of: 1) the proportion of women who experience complications by type of abortion method and type of abortion provider and 2) the proportion of women who obtain PAC by type of abortion method. These estimates were calculated separately for poor and non-poor women because these subgroups of women may have different abortion-seeking and treatment behaviors. We used this information to calculate the proportion of poor and non-poor women seeking treatment for induced abortion complications. Next, we weighted these proportions by the distribution of women of reproductive age in Kinshasa by poor and non-poor status to come up with the proportion of all women who have abortions who will receive treatment in health facilities. The inverse of this proportion is our multiplier or adjustment factor. This multiplier represents the number of women who have abortions for every woman who has an abortion and obtains PAC in a facility. A mathematical expression of the inputs and steps for calculating the multiplier can be found in In our initial calculation of the number of abortion complications, spontaneous or induced, treated in facilities, we obtained 95% confidence intervals around the estimate. To estimate the total number of induced abortions that occur in Kinshasa in 2016, we applied the multiplier to the number of induced abortion complications treated in health facilities . This calculation was done for the point estimate of abortion complications, as well as its lower and upper bounds, since these were obtained from a random sample of health facilities. We applied this to the estimates of induced abortions to enable us to provide lower and upper estimates of the number of induced abortions in Kinshasa. We then calculated the abortion rate by dividing the number of induced abortions by the population of women of reproductive age (15–49 years), and the abortion ratio by dividing the number of induced abortions by the number of live births in Kinshasa. By dividing the lower and upper estimates of the number of induced abortions by the reproductive-age population, we also obtained lower and upper estimates for the induced abortion rate.We estimated the annual number of pregnancies in Kinshasa by summing the annual number of live births, induced abortions, and miscarriages. Prior studies have demonstrated that the number of miscarriages is equal to the sum of 20% of live births and 10% of induced abortions , 27. ThuVariation exists in the average annual PAC caseloads by facility type . The PACAlthough median PAC caseloads are higher in public facilities, regardless of level of facility, the overwhelming majority of PAC, 90%, is provided by health centers in Kinshasa, and almost exclusively in the private/NGO sector . HospitaIn 2016, an estimated 60,870 women received PAC in health facilities across Kinshasa . From thApplying the multiplier (3.9) to the number of induced abortion complications treated, we estimated that 146,713 induced abortions took place in Kinshasa in 2016; our lower and upper estimates are 128,684 and 164,079 . We calcIn 2016, an estimated 563,064 pregnancies occurred in Kinshasa, resulting in a pregnancy rate of 241 per 1,000 women of reproductive age . UnintenLastly, we calculated the percentage distribution of all pregnancies by intention status and outcome: 33% are planned births, 27% unplanned births, 26% induced abortions, 7% miscarriages from intended pregnancies, and 8% miscarriages from unintended pregnancies . Thus, tThis article presents the first estimates of abortion incidence and unintended pregnancy in Kinshasa, DRC. We estimated that 146,713 induced abortions occur every year in Kinshasa, yielding an abortion rate of 56 per 1,000 women aged 15–49. We also calculated that more than 343,000 unintended pregnancies occur annually, resulting in an unintended pregnancy rate of 147 per 1,000 women aged 15–49. Taken together, these findings show that two in five unintended pregnancies end in abortion. Women in Kinshasa are clearly struggling to prevent unintended pregnancies, which often result in unwanted childbearing and abortion.In Kinshasa, the overwhelming majority of abortion complications are treated in lower-level facilities, specifically private or NGO-affiliated health centers. This differs from the pattern that is typically observed in countries where the AICM has been applied: Most women obtain PAC at higher-level facilities such as hospitals , 29, 30.The abortion rate in Kinshasa  is higher than the 2010–2014 rate for Middle Africa  . Given tEmerging evidence from many parts of sub-Saharan Africa indicate that growing numbers of women are using misoprostol to induce abortions –38. FindKinshasa has a relatively high rate of unintended pregnancy, 147 per 1,000 women ages 15–49, compared to other African countries . We estiSeveral limitations of this study are worth mentioning. First, the study team had difficulty compiling a complete and up-to-date list of all health facilities capable of providing PAC in Kinshasa. During the HFS fieldwork, we learned that several facilities were misclassified, either by level of facility , ownership (public of private/NGO), or both. Given that we had selected 100% of hospitals to be in our sampling frame, it is possible that some hospitals were not captured in our sample. This misclassification could have biased our estimate of the number of induced abortions downwards.Second, our estimation of the abortion rate is contingent on the number of reproductive-age women living in Kinshasa. The DRC has not conducted a census since 1984; thus, a recent, accurate count of the population does not exist. Instead, we relied on official population estimates produced from population projections of the last census conducted over three decades ago .Third, as is standard practice for the AICM, we assume that women do not seek treatment for first-trimester pregnancy losses and thus only subtract late miscarriages from the total number of treated abortion complications. If a substantial number of women obtain PAC for miscarriages of pregnancies at less than 13 weeks gestation, we may be subtracting too few spontaneous abortion complications from the total number of PAC cases, which would result in overestimates of the number of PAC cases due to induced abortion, as well as the number of abortions.Fourth, we assumed that all induced abortions were the result of unintended pregnancies. Some of these induced abortions, however, may have been intended at the time of conception. A woman may have later decided to abort the pregnancy because of a change in life circumstances, such as separation from her partner.Fifth, we did not provide HPS respondents with a formal definition of poor and non-poor women in Kinshasa when we asked respondents to provide responses by poverty status. It is possible that respondents used different definitions of poverty when formulating their responses to our questions.Finally, our estimate of the annual number of induced abortions in Kinshasa relies heavily on the multiplier that was calculated using data collected from HPS respondents. We selected informants deemed knowledgeable about the practice of abortion and the treatment of abortion complications in Kinshasa. It is important to recognize that respondents’ reports were based on their perceptions of the abortion situation; thus, the accuracy of the multiplier is dependent on the accuracy of their reports.Despite the DRC’s restrictive abortion law, thousands of women continue to obtain abortions every year in Kinshasa, of which many are performed unsafely, resulting in severe complications and sometimes death. Our study demonstrates that more effort is needed to reduce the number of unintended pregnancies and unsafe abortions that occur in Kinshasa. Doing so will reduce the number of women who suffer abortion complications and die needlessly from unsafe abortion.S1 File(DOCX)Click here for additional data file.