Search

Background: Finding duplicates is an important phase of systematic review. However, no consensus regarding the methods to find duplicates has been provided. This study aims to describe a pragmatic strategy of combining auto- and hand-searching duplicates in systematic review and to evaluate the prevalence and characteristics of duplicates. Methods and Findings: Literatures regarding portal vein thrombosis (PVT) and Budd-Chiari syndrome (BCS) were searched by the PubMed, EMBASE, and Cochrane library databases. Duplicates included one index paper and one or more redundant papers. They were divided into type-I (duplicates among different databases) and type-II (duplicate publications in different journals/issues) duplicates. For type-I duplicates, reference items were further compared between index and redundant papers. Of 10936 papers regarding PVT, 2399 and 1307 were identified as auto- and hand-searched duplicates, respectively. The prevalence of auto- and hand-searched redundant papers was 11.0% (1201/10936) and 6.1% (665/10936), respectively. They included 3431 type-I and 275 type-II duplicates. Of 11403 papers regarding BCS, 3275 and 2064 were identified as auto- and hand-searched duplicates, respectively. The prevalence of auto- and hand-searched redundant papers was 14.4% (1640/11403) and 9.1% (1039/11403), respectively. They included 5053 type-I and 286 type-II duplicates. Most of type-I duplicates were identified by auto-searching method (69.5%, 2385/3431 in PVT literatures; 64.6%, 3263/5053 in BCS literatures). Nearly all type-II duplicates were identified by hand-searching method (94.9%, 261/275 in PVT literatures; 95.8%, 274/286 in BCS literatures). Compared with those identified by auto-searching method, type-I duplicates identified by hand-searching method had a significantly higher prevalence of wrong items (47/2385 versus 498/1046, p<0.0001 in PVT literatures; 30/3263 versus 778/1790, p<0.0001 in BCS literatures). Most of wrong items originated from EMBASE database. Conclusion: Given the inadequacy of a single strategy of auto-searching method, a combined strategy of auto- and hand-searching methods should be employed to find duplicates in systematic review. [ABSTRACT FROM AUTHOR]

Sample size calculations are an important part of research to balance the use of resources and to avoid undue harm to participants. Effect sizes are an integral part of these calculations and meaningful values are often unknown to the researcher. General recommendations for effect sizes have been proposed for several commonly used statistical procedures. For the analysis of tables, recommendations have been given for the correlation coefficient for binary data; however, it is well known that suffers from poor statistical properties. The odds ratio is not problematic, although recommendations based on objective reasoning do not exist. This paper proposes odds ratio recommendations that are anchored to for fixed marginal probabilities. It will further be demonstrated that the marginal assumptions can be relaxed resulting in more general results. [ABSTRACT FROM AUTHOR]

The phenomenon of colour constancy in human visual perception keeps surface colours constant, despite changes in their reflected light due to changing illumination. Although colour constancy has evolved under a constrained subset of illuminations, it is unknown whether its underlying mechanisms, thought to involve multiple components from retina to cortex, are optimised for particular environmental variations. Here we demonstrate a new method for investigating colour constancy using illumination matching in real scenes which, unlike previous methods using surface matching and simulated scenes, allows testing of multiple, real illuminations. We use real scenes consisting of solid familiar or unfamiliar objects against uniform or variegated backgrounds and compare discrimination performance for typical illuminations from the daylight chromaticity locus (approximately blue-yellow) and atypical spectra from an orthogonal locus (approximately red-green, at correlated colour temperature 6700 K), all produced in real time by a 10-channel LED illuminator. We find that discrimination of illumination changes is poorer along the daylight locus than the atypical locus, and is poorest particularly for bluer illumination changes, demonstrating conversely that surface colour constancy is best for blue daylight illuminations. Illumination discrimination is also enhanced, and therefore colour constancy diminished, for uniform backgrounds, irrespective of the object type. These results are not explained by statistical properties of the scene signal changes at the retinal level. We conclude that high-level mechanisms of colour constancy are biased for the blue daylight illuminations and variegated backgrounds to which the human visual system has typically been exposed. [ABSTRACT FROM AUTHOR]

The objectives of this paper are to predict life years lost associated with obesity-related diseases (ORDs) for U.S. non-smoking adults, and to examine the relationship between those ORDs and mortality. Data from the National Health Interview Survey, 1997–2000, were used. We employed mixed proportional hazard models to estimate the association between those ORDs and mortality and used simulations to project life years lost associated with the ORDs. We found that obesity-attributable comorbidities are associated with large decreases in life years and increases in mortality rates. The life years lost associated with ORDs is more marked for younger adults than older adults, for blacks than whites, for males than females, and for the more obese than the less obese. Using U.S. non-smoking adults aged 40 to 49 years as an example to illustrate percentage of the life years lost associated with ORDs, we found that the mean life years lost associated with ORDs for U.S. non-smoking black males aged 40 to 49 years with a body mass index above 40 kg/m2 was 5.43 years, which translates to a 7.5% reduction in total life years. White males of the same age range and same degree of obesity lost 5.23 life years on average – a 6.8% reduction in total life years, followed by black females (5.04 years, a 6.5% reduction in life years), and white females (4.7 years, a 5.8% reduction in life years). Overall, ORDs increased chances of dying and lessened life years by 0.2 to 11.7 years depending on gender, race, BMI classification, and age. [ABSTRACT FROM AUTHOR]

Objective: To identify patterns of perception of front-of-pack (FOP) nutrition labels and determine dietary, lifestyle and health profiles related to such patterns. Design: Cross-sectional. Participants/Setting: 28,952 French adults participating in the web-based Nutrinet-Santé cohort. Outcome measures: Perception was measured using indicators of understanding and acceptability for three simple FOP labels (“green tick”, the logo of the French Nutrition and Health Program and “simple traffic lights” (STL)), and two detailed FOP formats (“multiple traffic lights” (MTL) and “color range” logo (CR)), placed on ready-to-eat soup packages. Dietary intake data were collected using three web-based 24 h records. Statistical analyses: Associations of perception patterns with individual characteristics, including diet, lifestyle and health status, were examined using analysis of covariance and logistic regression, adjusted for socio-demographic and economic factors. Results: No clear trend emerged concerning differences in dietary intake between perception groups. Low physical activity and obesity were more frequent in the ‘favorable to STL’ group (respectively, 20.7% and 10.7%). The ‘favorable to MTL’ group included the highest percentage of individuals who declared type 2 diabetes (2.2%). Persons with hypertension were proportionally more numerous in the ‘favorable to MTL’ and the ‘favorable to CR logo’ groups (respectively, 9.5% and 9.3%). Conclusions: After adjustment for socio-demographic and economic factors, no FOP label stood out as being more suitable than another for reaching populations with poor diet. However, both STL and MTL may be most appropriate for increasing awareness of healthy eating among groups at higher risk of nutrition-related chronic diseases. [ABSTRACT FROM AUTHOR]

Background: The neighborhood environment, as a determinant of walking, has been assessed in several developed countries. However, few studies have investigated these associations in Chinese populations. Objective: To examine the association between the perceived neighborhood environment and walking for recreation or transportation purposes among Chinese community residents. Methods: We used a multi-stage stratified random sampling design to conduct a cross-sectional study of 1528 Chinese adults in Shanghai. Environmental and walking variables were assessed using a revised Abbreviated Neighborhood Environment Walkability Scale for Chinese subjects and a long version of International Physical Activity Questionnaire. Self-reported demographic variables including gender, age, employment status, and location of community were also collected. Multiple logistic regression analysis was applied to examine the association between the neighborhood environment and walking. Results: Based on the results of IPAQ, 13.7% of the overall subjects were physical inactive, which was considered to be lowly active. For all participants, accessibility to services was significantly associated with walking for both recreation and transportation (odds ratio = 1.062, 95% confidence interval: 1.016, 1.110; odds ratio = 1.053; 95% confidence interval: 1.008, 1.100, respectively). In males, accessibility to services was significantly associated both with walking for recreation and walking for transportation. However, a significantly negative association was found between the neighborhood surroundings and walking for recreation. In contrast, females who perceived good traffic safety tended to walk for recreation. Data also revealed a difference between working and retired individuals. Among working participants, perceived environmental variables were not significantly associated with walking for recreation and transportation. Conclusions: The association between neighborhood environment and walking varied depending on the reason for walking and the characteristics of the participants. Our findings suggest that interventions to promote walking in community residents should include improving the neighborhood environment, particularly accessibility to services such as building more stores, parks, and public transit facilities. [ABSTRACT FROM AUTHOR]

Objective: There is increasing evidence that prevention programmes for type 2 diabetes mellitus (T2DM) and obesity need to consider individual and regional risk factors. Our objective is to assess the independent association of area level deprivation with T2DM and obesity controlling for individual risk factors in a large study covering the whole of Germany. Methods: We combined data from two consecutive waves of the national health interview survey ‘GEDA’ conducted by the Robert Koch Institute in 2009 and 2010. Data collection was based on computer-assisted telephone interviews. After exclusion of participants <30 years of age and those with missing responses, we included n = 33,690 participants in our analyses. The outcome variables were the 12-month prevalence of known T2DM and the prevalence of obesity (BMI ≥30 kg/m2). We also controlled for age, sex, BMI, smoking, sport, living with a partner and education. Area level deprivation of the districts was defined by the German Index of Multiple Deprivation. Logistic multilevel regression models were performed using the software SAS 9.2. Results: Of all men and women living in the most deprived areas, 8.6% had T2DM and 16.9% were obese (least deprived areas: 5.8% for T2DM and 13.7% for obesity). For women, higher area level deprivation and lower educational level were both independently associated with higher T2DM and obesity prevalence [highest area level deprivation: OR 1.28 (95% CI: 1.05–1.55) for T2DM and OR 1.28 (95% CI: 1.10–1.49) for obesity]. For men, a similar association was only found for obesity [OR 1.20 (95% CI: 1.02–1.41)], but not for T2DM. Conclusion: Area level deprivation is an independent, important determinant of T2DM and obesity prevalence in Germany. Identifying and targeting specific area-based risk factors should be considered an essential public health issue relevant to increasing the effectiveness of diabetes and obesity prevention. [ABSTRACT FROM AUTHOR]

The recent interest in network analysis applications in personality psychology and psychopathology has put forward new methodological challenges. Personality and psychopathology networks are typically based on correlation matrices and therefore include both positive and negative edge signs. However, some applications of network analysis disregard negative edges, such as computing clustering coefficients. In this contribution, we illustrate the importance of the distinction between positive and negative edges in networks based on correlation matrices. The clustering coefficient is generalized to signed correlation networks: three new indices are introduced that take edge signs into account, each derived from an existing and widely used formula. The performances of the new indices are illustrated and compared with the performances of the unsigned indices, both on a signed simulated network and on a signed network based on actual personality psychology data. The results show that the new indices are more resistant to sample variations in correlation networks and therefore have higher convergence compared with the unsigned indices both in simulated networks and with real data. [ABSTRACT FROM AUTHOR]

When asked to randomly select answer choices on easy multiple choice questions, people select more correct answers than expected by chance. Sparrow and Wegner showed that this tendency was eliminated if participants answered questions correctly before answering randomly. They argued that answering a question correctly unprimes the tendency to choose the correct answer, thereby reducing the correct response rate close to the chance level of.5. An alternative explanation, consistent with these results, is that answering questions correctly provides a baseline, which allows participants to strategize, i.e., to match and mismatch equal numbers of their purportedly random responses to the baseline response. Three studies showed that the presence of a baseline, even when unpriming is not feasible, led to lower correct response rates than those obtained in a condition in which no baseline was available. Furthermore, the presence of a baseline led to more nonrandom sequences of correct and incorrect responses. One specific sequence–alternating correct and incorrect answers–mediated the relation between the presence of a baseline and lower correct response rate. These findings suggest that strategizing, not unpriming, accounts for Sparrow and Wegner’s results. [ABSTRACT FROM AUTHOR]

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system. [ABSTRACT FROM AUTHOR]

Purpose: The variational Bayesian independent component analysis-mixture model (VIM), an unsupervised machine-learning classifier, was used to automatically separate Matrix Frequency Doubling Technology (FDT) perimetry data into clusters of healthy and glaucomatous eyes, and to identify axes representing statistically independent patterns of defect in the glaucoma clusters. Methods: FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal FDT results from the UCSD-based Diagnostic Innovations in Glaucoma Study (DIGS) and African Descent and Glaucoma Evaluation Study (ADAGES). For all eyes, VIM input was 52 threshold test points from the 24-2 test pattern, plus age. Results: FDT mean deviation was −1.00 dB (S.D. = 2.80 dB) and −5.57 dB (S.D. = 5.09 dB) in FDT-normal eyes and FDT-abnormal eyes, respectively (p<0.001). VIM identified meaningful clusters of FDT data and positioned a set of statistically independent axes through the mean of each cluster. The optimal VIM model separated the FDT fields into 3 clusters. Cluster N contained primarily normal fields (1109/1190, specificity 93.1%) and clusters G1 and G2 combined, contained primarily abnormal fields (651/786, sensitivity 82.8%). For clusters G1 and G2 the optimal number of axes were 2 and 5, respectively. Patterns automatically generated along axes within the glaucoma clusters were similar to those known to be indicative of glaucoma. Fields located farther from the normal mean on each glaucoma axis showed increasing field defect severity. Conclusions: VIM successfully separated FDT fields from healthy and glaucoma eyes without a priori information about class membership, and identified familiar glaucomatous patterns of loss. [ABSTRACT FROM AUTHOR]

Background: Ovarian cancer is the most lethal gynecologic disease in the United States, with more women dying from this cancer than all gynecological cancers combined. Ovarian cancer has been termed the “silent killer” because some patients do not show clear symptoms at an early stage. Currently, there is a lack of approved and effective early diagnostic tools for ovarian cancer. There is also an apparent severe knowledge gap of ovarian cancer in general and of its indicative symptoms among both public and many health professionals. These factors have significantly contributed to the late stage diagnosis of most ovarian cancer patients (63% are diagnosed at Stage III or above), where the 5-year survival rate is less than 30%. The paucity of knowledge concerning ovarian cancer in the United States is unknown. Methods: The present investigation examined current public awareness and knowledge about ovarian cancer. The study implemented design strategies to develop an unbiased survey with quality control measures, including the modern application of multiple statistical analyses. The survey assessed a reasonable proxy of the US population by crowdsourcing participants through the online task marketplace Amazon Mechanical Turk, at a highly condensed rate of cost and time compared to traditional recruitment methods. Conclusion: Knowledge of ovarian cancer was compared to that of breast cancer using repeated measures, bias control and other quality control measures in the survey design. Analyses included multinomial logistic regression and categorical data analysis procedures such as correspondence analysis, among other statistics. We confirmed the relatively poor public knowledge of ovarian cancer among the US population. The simple, yet novel design should set an example for designing surveys to obtain quality data via Amazon Mechanical Turk with the associated analyses. [ABSTRACT FROM AUTHOR]

Background: Advancements in knowledge of obesity aetiology and mobile phone technology have created the opportunity to develop an electronic tool to predict an infant’s risk of childhood obesity. The study aims were to develop and validate equations for the prediction of childhood obesity and integrate them into a mobile phone application (App). Methods and Findings: Anthropometry and childhood obesity risk data were obtained for 1868 UK-born White or South Asian infants in the Born in Bradford cohort. Logistic regression was used to develop prediction equations (at 6±1.5, 9±1.5 and 12±1.5 months) for risk of childhood obesity (BMI at 2 years >91st centile and weight gain from 0–2 years >1 centile band) incorporating sex, birth weight, and weight gain as predictors. The discrimination accuracy of the equations was assessed by the area under the curve (AUC); internal validity by comparing area under the curve to those obtained in bootstrapped samples; and external validity by applying the equations to an external sample. An App was built to incorporate six final equations (two at each age, one of which included maternal BMI). The equations had good discrimination (AUCs 86–91%), with the addition of maternal BMI marginally improving prediction. The AUCs in the bootstrapped and external validation samples were similar to those obtained in the development sample. The App is user-friendly, requires a minimum amount of information, and provides a risk assessment of low, medium, or high accompanied by advice and website links to government recommendations. Conclusions: Prediction equations for risk of childhood obesity have been developed and incorporated into a novel App, thereby providing proof of concept that childhood obesity prediction research can be integrated with advancements in technology. [ABSTRACT FROM AUTHOR]

Objectives: To examine the factor structure and to evaluate the longitudinal measurement invariance of the demand-control-support questionnaire (DCSQ), using the Swedish Longitudinal Occupational Survey of Health (SLOSH). Methods: A confirmatory factor analysis (CFA) and multi-group confirmatory factor analysis (MGCFA) models within the framework of structural equation modeling (SEM) have been used to examine the factor structure and invariance across time. Results: Four factors: psychological demand, skill discretion, decision authority and social support, were confirmed by CFA at baseline, with the best fit obtained by removing the item repetitive work of skill discretion. A measurement error correlation (0.42) between work fast and work intensively for psychological demands was also detected. Acceptable composite reliability measures were obtained except for skill discretion (0.68). The invariance of the same factor structure was established, but caution in comparing mean levels of factors over time is warranted as lack of intercept invariance was evident. However, partial intercept invariance was established for work intensively. Conclusion: Our findings indicate that skill discretion and decision authority represent two distinct constructs in the retained model. However removing the item repetitive work along with either work fast or work intensively would improve model fit. Care should also be taken while making comparisons in the constructs across time. Further research should investigate invariance across occupations or socio-economic classes. [ABSTRACT FROM AUTHOR]

The aim of the present study was to explore if observer rated sleepiness (ORS) is a feasible method for quantification of driver sleepiness in field studies. Two measures of ORS were used: (1) one for behavioural signs based on facial expression, body gestures and body movements labelled B-ORS, and (2) one based on driving performance e.g. if swerving and other indicators of impaired driving occurs, labelled D-ORS. A limited number of observers sitting in the back of an experimental vehicle on a motorway about 2 hours repeatedly 3 times per day (before lunch, after lunch, at night) observed 24 participant’s sleepiness level with help of the two observer scales. At the same time the participant reported subjective sleepiness (KSS), EOG was recorded (for calculation of blink duration) and several driving measure were taken and synchronized with the reporting. Based on mixed model Anova and correlation analysis the result showed that observer ratings of sleepiness based on drivers’ impaired performance and behavioural signs are sensitive to extend the general pattern of time awake, circadian phase and time of driving. The detailed analysis of the subjective sleepiness and ORS showed weak correspondence on an individual level. Only 16% of the changes in KSS were predicted by the observer. The correlation between the observer ratings based on performance (D-ORS) and behavioural signs (B-ORS) are high (r = .588), and the B-ORS shows a moderately strong association (r = .360) with blink duration. Both ORS measures show an association (r>0.45) with KSS, whereas the association with driving performance is weak. The results show that the ORS-method detects the expected general variations in sleepy driving in field studies, however, sudden changes in driver sleepiness on a detailed level as 5 minutes is usually not detected; this holds true both when taking into account driving behaviour or driver behavioural signs. [ABSTRACT FROM AUTHOR]

Sampling techniques such as Respondent-Driven Sampling (RDS) are widely used in epidemiology to sample “hidden” populations, such that properties of the network can be deduced from the sample. We consider how similar techniques can be designed that allow the discovery of the structure, especially the community structure, of networks. Our method involves collecting samples of a network by random walks and reconstructing the network by probabilistically coalescing vertices, using vertex attributes to determine the probabilities. Even though our method can only approximately reconstruct a part of the original network, it can recover its community structure relatively well. Moreover, it can find the key vertices which, when immunized, can effectively reduce the spread of an infection through the original network. [ABSTRACT FROM AUTHOR]

Though the HIV/AIDS epidemic in Southeastern Europe is one of low reported prevalence, numerous studies have described the pervasiveness of medical providers’ lack of knowledge of HIV/AIDS in the Balkans. This study sought to culturally adapt an instrument to assess medical providers’ knowledge of and attitudes towards HIV/AIDS in Albania. Cultural adaptation was completed through development of a survey from previously validated instruments, translation of the survey into Albanian, blinded back translation, expert committee review of the draft instrument, focus group pre-testing with community- and University Hospital Center of Tirana-based physicians and nurses, and test-retest reliability testing. Blinded back translation of the instrument supported the initial translation with slight changes to the idiomatic and conceptual equivalences. Focus group pre-testing generally supported the instrument, yet some experiential and idiomatic changes were implemented. Based on unweighted kappa and/or prevalence adjusted bias adjusted kappa (PABAK), 20 of the 43 questions were deemed statistically significant at kappa and/or PABAK ≥0.5, while 12 others did not cross zero on the 95% confidence interval for kappa, indicating their probable significance. Subsequently, an instrument to assess medical providers’ knowledge of and attitudes toward HIV/AIDS for an Albanian population was developed which can be expanded within Albania and potentially to other countries within the Balkans, which have an Albanian-speaking population. [ABSTRACT FROM AUTHOR]

Background: Innovative models of care are required to cope with the ever-increasing number of patients on antiretroviral therapy in the most affected countries. This study, in Khayelitsha, South Africa, evaluates the effectiveness of a group-based model of care run predominantly by non-clinical staff in retaining patients in care and maintaining adherence. Methods and Findings: Participation in “adherence clubs” was offered to adults who had been on ART for at least 18 months, had a current CD4 count >200 cells/ml and were virologically suppressed. Embedded in an ongoing cohort study, we compared loss to care and virologic rebound in patients receiving the intervention with patients attending routine nurse-led care from November 2007 to February 2011. We used inverse probability weighting to estimate the intention-to-treat effect of adherence club participation, adjusted for measured baseline and time-varying confounders. The principal outcome was the combination of death or loss to follow-up. The secondary outcome was virologic rebound in patients who were virologically suppressed at study entry. Of 2829 patients on ART for >18 months with a CD4 count above 200 cells/µl, 502 accepted club participation. At the end of the study, 97% of club patients remained in care compared with 85% of other patients. In adjusted analyses club participation reduced loss-to-care by 57% (hazard ratio [HR] 0.43, 95% CI = 0.21–0.91) and virologic rebound in patients who were initially suppressed by 67% (HR 0.33, 95% CI = 0.16–0.67). Discussion: Patient adherence groups were found to be an effective model for improving retention and documented virologic suppression for stable patients in long term ART care. Out-of-clinic group-based models facilitated by non-clinical staff are a promising approach to assist in the long-term management of people on ART in high burden low or middle-income settings. [ABSTRACT FROM AUTHOR]

Background: The demographic transition in South Asia coupled with unplanned urbanization and lifestyle changes are increasing the burden of non-communicable disease (NCD) where infectious diseases are still highly prevalent. The true magnitude and impact of this double burden of disease, although predicted to be immense, is largely unknown due to the absence of recent, population-based longitudinal data. The present study was designed as a unique ‘Framingham-like’ Pakistan cohort with the objective of measuring the prevalence and risk factors for hypertension, obesity, diabetes, coronary artery disease and hepatitis B and C infection in a multi-ethnic, middle to low income population of Karachi, Pakistan. Methods: We selected two administrative areas from a private charitable hospital’s catchment population for enrolment of a random selection of cohort households in Karachi, Pakistan. A baseline survey measured the prevalence and risk factors for hypertension, obesity, diabetes, coronary artery disease and hepatitis B and C infection. Results: Six hundred and sixty-seven households were enrolled between March 2010 and August 2011. A majority of households lived in permanent structures (85%) with access to basic utilities (77%) and sanitation facilities (98%) but limited access to clean drinking water (68%). Households had high ownership of communication technologies in the form of cable television (69%) and mobile phones (83%). Risk factors for NCD, such as tobacco use (45%), overweight (20%), abdominal obesity (53%), hypertension (18%), diabetes (8%) and pre-diabetes (40%) were high. At the same time, infectious diseases such as hepatitis B (24%) and hepatitis C (8%) were prevalent in this population. Conclusion: Our findings highlight the need to monitor risk factors and disease trends through longitudinal research in high-burden transition communities in the context of rapid urbanization and changing lifestyles. They also demonstrate the urgency of public health intervention programs tailored for these transition communities. [ABSTRACT FROM AUTHOR]