Moderate Risk Class Research Articles

A latent class analysis of multiple health-risk behaviours among Portuguese college students

Traditionally, the prevalence of health-risk behaviours is high among university students. Although these behaviours are often analysed in isolation, there is likely evidence for the co-occurrence of multiple risk behaviours. In this study, a latent class analysis (LCA) was conducted with cross-sectional data from 840 Portuguese students (55.4% female) to explore patterns of multiple risk behaviours across seven behavioural dimensions (alcohol consumption, smoking, unhealthy eating, sedentary behaviour, risky sexual practices, illicit drug use, and self-medication). Additionally, a latent class regression was performed to explore predictors (perceived well-being and sociodemographic and academic characteristics) for each behavioural pattern. A three-class model emerged with different probabilities of risk: Low-risk behaviours (51.4%), Moderate-risk behaviors (14.9%), and High-risk behaviours (33.7%). Students with better perceptions of well-being and health were likelier to be in the healthier class. Students in the low- and moderate-risk classes were more likely to be in their first year of study, not in a romantic relationship and to be full-time students. Students who had not changed residence at the beginning of their studies and were female were more likely to be in the healthiest class. This study provides essential strategies for health promotion among university students, offering crucial insights for the design of effective health promotion interventions, especially targeted at specific groups of students with similar patterns of multiple risk behaviours.

Associations between healthy lifestyle behavioral patterns and mental health problems: A latent class analysis of 161,744 Chinese young adults

BackgroundYouth mental health problems are a public health priority. Multiple healthy lifestyle behaviors may cluster into healthy lifestyle behavioral patterns (HLBPs) that increase mental health risks in adolescents and older adults, but little is known regarding young adults. This study aimed to explore the associations between cluster HLBPs and mental health problems in young adults. MethodsWe selected 161,744 young adults aged 20–39 as participants from the database of a Chinese general hospital health management center for the years 2015–2020. The latent class analysis was used to identify HLBPs. ResultsA total of 15.0 % of young adults have at least one mental health problem. Five clusters of HLBPs were identified, characterized as low-risk class (1.6 %), moderate-risk class 1 (12.0 %), moderate-risk class 2 (2.1 %), moderate-risk class 3 (56.8 %), and high-risk class (27.4 %). The odds ratios (ORs) for young adults with two mental health problems increased with the risk grade of HLBPs, while the ORs for young adults with one or three mental health problems ranged from high to low according to the risk grade of HLBPs: high-risk class, moderate-risk class 2, moderate-risk class 3, moderate-risk class 1. LimitationsCross-sectional design and no causal conclusions could be drawn. ConclusionYoung adults demonstrated a cluster phenomenon of healthy lifestyle behaviors and significant associations between HLBPs and mental health problems. Young adults with a higher risk grade for HLBPs were more likely to have mental health problems. Different HLBPs should be taken into account when implementing mental health interventions.

The effect of smoking on latent hazard classes of metabolic syndrome using latent class causal analysis method in the Iranian population

BackgroundThe prevalence of metabolic syndrome is increasing worldwide. Clinical guidelines consider metabolic syndrome as an all or none medical condition. One proposed method for classifying metabolic syndrome is latent class analysis (LCA). One approach to causal inference in LCA is using propensity score (PS) methods. The aim of this study was to investigate the causal effect of smoking on latent hazard classes of metabolic syndrome using the method of latent class causal analysis.MethodsIn this study, we used data from the Tehran Lipid and Glucose Cohort Study (TLGS). 4857 participants aged over 20 years with complete information on exposure (smoking) and confounders in the third phase (2005–2008) were included. Metabolic syndrome was evaluated as outcome and latent variable in LCA in the data of the fifth phase (2014–2015). The step-by-step procedure for conducting causal inference in LCA included: (1) PS estimation and evaluation of overlap, (2) calculation of inverse probability-of-treatment weighting (IPTW), (3) PS matching, (4) evaluating balance of confounding variables between exposure groups, and (5) conducting LCA using the weighted or matched data set.ResultsBased on the results of IPTW which compared the low, medium and high risk classes of metabolic syndrome (compared to a class without metabolic syndrome), no association was found between smoking and the metabolic syndrome latent classes. PS matching which compared low and moderate risk classes compared to class without metabolic syndrome, showed that smoking increases the probability of being in the low-risk class of metabolic syndrome (OR: 2.19; 95% CI: 1.32, 3.63). In the unadjusted analysis, smoking increased the chances of being in the low-risk (OR: 1.45; 95% CI: 1.01, 2.08) and moderate-risk (OR: 1.68; 95% CI: 1.18, 2.40) classes of metabolic syndrome compared to the class without metabolic syndrome.ConclusionsBased on the results, the causal effect of smoking on latent hazard classes of metabolic syndrome can be different based on the type of PS method. In adjusted analysis, no relationship was observed between smoking and moderate-risk and high-risk classes of metabolic syndrome.

FLOOD RISK OF GRASSLANDS IN THE MOUNTAIN AREA OF WESTERN ROMANIA

Floods, some of the most destructive natural phenomena, are occurring with increasing frequency, against the backdrop of climate change in recent years. Floods affect both built spaces and natural areas, implicitly the lands used as grasslands. In the context outlined above, the purpose of this study is to identify grasslands susceptible to being affected by floods and to group and map them according to the intensity of the manifestation of the flood risk. For the flood risk assessment, both for the entire analyzed area and for the grassland areas, in the GIS environment, seven factors (spatialized in raster format) determining the occurrence of floods were taken into account: land use, altitude, slope, drainage density, rainfall, distance to rivers and distance to roads. The flood vulnerability map of the analyzed territory, implicitly of the grassland areas, obtained by summing up and the weighted participation of the seven variables, was reclassified into five risk classes/areas: no risk or very low risk, low risk, medium risk, high risk and very high risk. It has been shown that the most vulnerable are the surfaces located on land with low slopes, located at low altitudes and in the proximity of water courses. Regarding the areas of grasslands, 50% fall into the classes without flood risk, with very low and low risk, 28% in the moderate risk class, 16% present a high risk and 6% of the grasslands are classified in the risk class very high to floods. From the point of view of practical applicability, it is important to identify and map the grasslands at risk of flooding, so that measures can be taken to mitigate the destructive effects.

Evaluation of Liquefaction Potential Index and Severity Mapping for Rangpur City Corporation

This paper aims to investigate the Liquefaction Potential Index (LPI) of different Wards and prepare a liquefaction severity map of Rangpur City Corporation. A Liquefaction severity map of a city helps the legislators and policymakers with informed land use planning as well as the development of the town. Disturbed soils from 10 Wards among 33 Wards of Rangpur were collected for different depths in a single borehole. The locations for the borehole were selected based on the seismic soil profile and engineering geology reports available for Rangpur City Corporation in CDMP-II. Standard Penetration Test (SPT) and Microtremor test were done on the field. Then, the Grain Size Distribution test and Liquefaction Potential Index (LPI) were determined for the collected samples in the laboratory. Based on the results of the tests done in the field and laboratory, the severity was classified as moderate, moderate to severe, and severe. Based on the Liquefaction Potential Index (LPI) value, four Wards of Rangpur City Corporation fall within the moderate risk class, three Wards show moderate to severe risk of liquefaction, and the remaining 3 Wards belong to the severe risk class.
 J. of Sci. and Tech. Res. 4(1): 49-58, 2022

Assessment of two methods on zoning wildfire propagation in Itacolomi State Park, Minas Gerais State, Brazil

This study aimed to assess the wild fire propagation risk to wildfires in the Itacolomi State Park, in Minas Gerais State, Brazil, using GIS and to compare the efficiency of the incident solar radiation over the aspect variable. The following variables were used: land cover/use (LCU), slope (SLP), slope curvature (CUR), aspect (ASP) and incident solar radiation (SOL). The weights of each variable were calculated from the ratio between the total area and the burned area of each class in order to generate the fire propagation risk maps. Fire data from 2016 to 2019 were used for validation. When the moderate risk class was considered susceptible, inadequate precision was observed for both methods (ASP and SOL). On the other hand, when the moderate class was considered non-susceptible to fire, the results presented moderate accuracy. Furthermore, the methods using SOL and ASP showed similar results. The results can guide fire mitigation actions on the park.

Patterns of psychological pain and self-harm behaviors in adolescents.

The study examined the role of campus stressors and psychological pain on non-suicidal self-injury (NSSI) and suicide attempt (SA). Specific patterns of co-occurring psychological pain, campus stressors, and self-harm behaviors were identified by latent profile analysis, and their odds ratios (ORs) on NSSI and SA were analyzed in cross-sectional study and 2-year follow-up study. Structural Equation Model was used to explore indirect effect of campus stressors on SA and NSSI via different components of psychological pain. Three classes were identified as low-risk class (68.58%) with low endorsements on the three measures, moderate-risk class (26.52%) with the elevated academic stressors, high levels of painful feelings, and high probabilities on NSSI; and high-risk class (4.90%) with the elevated combined stressors, high levels of pain avoidance, and high probabilities on SA. Compared to the moderate-risk class, adolescents in the high-risk class had a 4.97 OR of reporting NSSI, 17.98 OR of reporting SA. Pain avoidance class at baseline reported a higher probability in SA class (OR=224.00) in a 2-year study. Painful feelings might be shared psychosocial correlates for NSSI and SA. However, pain avoidance may play a role in distinguishing SA from NSSI, which shed light on the intervention of adolescents who engage in self-harm behaviors.

Association Between the Patterns of Five Unhealthy Behaviors and Suicidal Behaviors Among Adolescents in Six Provinces of China.

BackgroundIn adolescents, multiple unhealthy behaviors frequently occur together and are likely to be associated with suicidal behaviors (SBs), increasing the risk of suicide. This study aimed to clarify the potential patterns of unhealthy behaviors in Chinese adolescents and to examine the associations between the different patterns of unhealthy behaviors and SBs.MethodsA total of 22,628 middle school students were enrolled in this study. Self-reported unhealthy behaviors and SBs were investigated using questionnaires. Latent class analysis (LCA) was performed based on five unhealthy behaviors [smoking, alcohol use (AU), diet pill use (DPU), screen time (ST), and problematic mobile phone use (PMPU)]. Multivariate logistic regressions were used to examine associations between the different patterns of unhealthy behaviors and SBs.ResultsFour subgroups of unhealthy behaviors were identified by LCA, including high-risk class (smoking/AU/DPU/PMPU/ST), moderate-risk class 1 (DPU/PMPU), moderate-risk class 2 (smoking/AU/ST), and low-risk class. Compared with the low-risk class, moderate-risk class 1, moderate-risk class 2, and high-risk class had higher risks of suicidal ideation, suicide plan, and suicide attempt.ConclusionsThese findings suggested that patterns of unhealthy behaviors were related to SBs in Chinese adolescents. Accordingly, considerations of different classes of unhealthy behaviors may be essential for developing effective preventive programs.

Multiple lifestyle risk behaviours and hierarchical dimensions of psychopathology in 6640 Australian adolescents.

Physical inactivity, sugar sweetened beverage consumption, alcohol use, smoking, poor sleep and excessive recreational screen time (the 'Big 6' lifestyle risk behaviours) often co-occur and are key risk factors for psychopathology. However, the best fitting latent structure of the Big 6 is unknown and links between multiple lifestyle risk behaviours and hierarchical dimensions of psychopathology have not been explored among adolescents. This study aimed to address these gaps in the literature. Confirmatory factor analysis, latent class analysis and factor mixture models were conducted among 6640 students (Mage = 12.7 years) to identify the latent structure of the Big 6 lifestyle risk behaviours. Structural equation models were then used to examine associations with psychopathology. A mixture model with three classes, capturing mean differences in a single latent factor indexing overall risk behaviours, emerged as the best fitting model. This included relatively low-risk (Class 1: 30%), moderate-risk (Class 2: 67%) and high-risk (Class 3: 3%) classes. Students high on externalizing demonstrated significantly greater odds of membership to the high-risk class (odds ratio = 8.75, 99% confidence interval = [3.30, 23.26]) and moderate-risk class (odds ratio = 2.93, 99% confidence interval = [1.43, 5.97]) in comparison to the low-risk class. Similarly, students high on internalizing demonstrated significantly higher odds of membership to the high-risk class (odds ratio = 1.89, 99% confidence interval = [1.06, 3.37]) and the moderate-risk class (odds ratio = 1.66, 99% confidence interval = [1.03, 2.67]) in comparison to the low-risk class. Associations between lower order factors of psychopathology and lifestyle risk behaviours were mostly accounted for by the more parsimonious higher order factors. Classes representing differences in probabilities of the Big 6 lifestyle risk behaviours relate to varying levels of hierarchical dimensions of psychopathology, suggesting multiple health behaviour change and transdiagnostic intervention approaches may be valuable for reducing risk of psychopathology.

Change in suicidal ideation and associated factors among young adults in Hong Kong from 2018 to 2019: a latent transition analysis.

PurposeSuicide in young adulthood is a vital public health concern. There have been few systematic studies that examined the prevalence and transition of suicidal ideation classes in young adults and the factors associated with the transition.MethodsThis two-wave survey recruited 1269 young adults (Mean age = 24.0 years, 70.1% males) in Hong Kong. The participants completed the Suicidal Ideation Attributes Scale, Chinese Health Questionnaire, and help-seeking behaviors in 2018 and 2019. Latent profile analysis was used to classify the participants into latent classes of suicidal ideation with substantive checking under the 3-step approach. Latent transition analysis with measurement invariance examined the transition among the latent classes from 2018 to 2019 and the associations with help-seeking behaviors and change in psychological distress.ResultsThree latent classes of suicidal ideation were identified and over two-thirds of the participants belonged to the Low-risk class with minimal suicidal ideation. The prevalence of the High-risk class dropped from 10.2 to 7.2%, while that of the Moderate-risk class remained stable from 2018 to 2019. Increases in psychological distress predicted higher probabilities to remain at or transit into more risky classes. Engagement in help-seeking behaviors showed differential transitions in suicidal ideation across time.ConclusionThe findings suggest three latent classes of suicidal ideation with distinct profiles among the young adults. Deterioration in psychological distress showed a temporal effect on worsening of suicidal ideation over a 1-year period. Future studies should elucidate the comparative effectiveness of help-seeking behaviors via online and offline channels.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00127-021-02203-9.

Development of an Index to Measure West Nile Virus Transmission Risk in New Jersey Counties

We developed an index for use by New Jersey counties to measure West Nile virus (WNV) transmission risk to the human population. We used a latent profile analysis to develop the index, identifying categories of environmental conditions associated with WNV transmission risk to humans. The final model included 4 indicators of transmission risk: mosquito abundance and minimum field infection rate, temperature, and human case count. We used data from 2004 to 2018 from all 21 New Jersey counties aggregated into 11 2-wk units per county per year (N = 3,465). Three WNV risk classes were identified. The Low Risk class had low levels of all variables. The Moderate Risk class had high abundance, average temperature levels, and low levels of the other variables. The High Risk class had substantially above average human case likelihood, average temperature, and high mosquito infection rates. These results suggest the presence of 3 distinct WNV risk profiles, which can be used to guide the development of public health actions intended to mitigate WNV transmission risk to the human population.

A Longitudinal Analysis of Alcohol Use Behavior among Korean Adults and Related Factors: A Latent Class Growth Model.

This study classified the changes in alcohol use behavior among Korean adults and explored the related factors. The study used data from the 4th (2009) to 14th (2019) waves of the Korean Welfare Panel Study. The subjects were 8267 adults aged 19–60 years. Latent class growth analysis was used to classify the latent classes of alcohol use behavior among Korean adults, and logistic regression analysis was performed to identify the specific factors that form the classes. Additionally, the 11-year trajectories of major variables associated with alcohol use behavior for the derived classes were analyzed using growth mixture modeling. Four classes were identified according to the trajectories of alcohol use behavior. There were statistically significant differences in the trajectories of depression, self-esteem, satisfaction in family relationships, and satisfaction in leisure activities according to the class of alcohol use behavior. In particular, self-esteem and satisfaction in family relationships indicated distinctly decreasing trajectories in the low- to moderate-risk class, which suggested the need for longitudinal analysis of the factors that influence alcohol use behavior. Moreover, it is recommended that interventions for the prevention of high-risk drinking target not only individuals but also family units.

Serum carcinoembryonic antigen pre-operative level in colorectal cancer: revisiting risk stratification.

Biomarkers may play a role as predictive and prognostic factors in colorectal cancer patients. The aims of the study were to verify the prognostic role of pre-operative serum carcinoembryonic antigen (CEA) level in predicting overall survival and risk of recurrence in a cohort of colorectal cancer patients and to evaluate optimal cut-off values. A retrospective cohort analysis was performed on colorectal cancer patients undergoing elective curative surgery between 2004 and 2019 at an Italian Academic Hospital. Main outcomes were overall survival, disease-free survival at 3-years and risk of local, loco-regional and distant recurrence during follow-up. A receiver operating characteristic (ROC) curve analysis was plotted using CEA pre-operative values and follow-up data in order to estimate the optimal cut-off values. A total of 559 patients were considered. The mean CEA value was 12.1 ± 54.1ng/mL, and the median 29.3 (0-4995) ng/mL. The ROC curve analysis identified 12.5ng/mL as the best CEA cut-off value to predict the risk of metastatic development after surgery in stage I-III colorectal cancer patients, and 10ng/mL as the best CEA cut-off value to predict overall survival and disease-free survival in stage III-IV patients. These data suggest a stratification of colorectal cancer patients in three classes of risk: a low risk class (CEA <10 ng/mL), a moderate risk class (CEA 10-12.5 ng/mL) and a high risk class (CEA >12.5 ng/mL). In conclusion, pre-operative serum CEA measurements could integrate information to enhance patient risk stratification and tailored therapy.

Human health risk assessment of arsenic and trace metals in atmospheric dust of Arak industrial area, Iran.

In order to investigate concentrations, variability, sources, and human health risk of trace elements, 38 atmospheric dust samples were collected around Arak industrial area. The average concentrations of Cd~Zn, As, and Pb were 3.3, 2.5, and 2.4 times higher than the corresponding geochemical background, respectively, while concentrations of Co, Cu, Ni, and Hg were lower. Based on geo-accumulation index (Igeo), trace elements were classified between practically uncontaminated to moderate contaminated levels. The potential risk (RI) map showed that about 86% of the study area for all trace elements was in the moderate risk class. According to the results of positive matrix factorization (PMF) model, four factors were extracted for trace elements, including industrial sources, natural sources, mining, and transportation, that contributed about 30, 27, 26, and 17% to pollution of the area, respectively. The carcinogenic risks for inhalation exposure to Cd, As, Ni, and Co were lower than the permissible risk limit than the EPA recommend (10-6), indicating an acceptable level of risk. Results of the health risk evaluation indicated that the non-carcinogenic health risk (i.e., hazard quotient, HQ) for children and adults decrease following: As > Pb > Ni > Zn > Cd > Cu > Co > Hg. When excluding As, the hazard index (HI) was lower than the safe level (HI < 1) for all the trace elements, whereas HQ values of As for children and adults were 17.1 and 1.6, respectively, indicating a potential risk for children. In sum, several remedial actions to eliminate or to reduce the dust pollution are urgently required in the industrial area of Arak.

A latent class analysis of psychological symptoms and health risk behaviors among Chinese adolescents.

Multiple health risk behaviors (HRBs) tend to co-occur which increase risks of mental disorder. In this study, we identified the association between latent class of HRBs and psychological symptoms in Chinese adolescents. We assessed 22 628 Chinese adolescents from November 2015 to January 2016. The average age of the students were (15.36 ± 1.79), among which there were 10 990 male students and 11 638 female students. A latent class analysis was applied to identity HRBs patterns. The multivariable logistic regression models were utilized to examine the association between HRBs patterns and psychological symptoms. Four latent classes were identified, characterized as low-risk class, moderate-risk class 1 (smoking/ alcohol use (AU)/screen time (ST)), moderate-risk class 2 (unhealthy losing weight (ULW)/ problematic mobile phone use (PMPU)), and high-risk class (ULW/smoking/AU/ST/ PMPU), which were 71.2 %, 3.2 %, 22.3 %, and 3.3 % of involved participants, respectively. Compared to the low-risk class, moderate-risk class 1, moderate-risk class 2, and high-risk class showed that adjusted OR (95 %CI) value of 1.97 (1.68-2.32), 3.98 (3.72-4.26) and 6.38 (CI: 5.47-7.44) were significantly associated with psychological symptoms (P < 0.001 for each). Our findings indicated that identifying different latent class of HRBs would be helpful for the design of tailored interventions, and prevention of different patterns of HRBs should be considered in the implementation of effective intervention programs related to psychological symptoms.

Flash flood risk assessment using geospatial technology in Shewa Robit town, Ethiopia

Flash flood is an extreme flooding event which is quick, short-lived, hazardous phenomena having negative environmental and socio-economic impacts. Flood risk management is essential to reduce the effects of flood on human lives and livelihoods. The main goals of this research were flash flood risk analysis and risk quantification in terms of land use land cover using geo-spatial technology in Shewa Robit town. In the present study, elevation, slope, drainage density, distance from river, NDVI, land use land cover, topographic wetness index and curvature were used as parameters determining flash flood risk. To realize these research objectives, all these data were reclassified in to five classes and different weights for each of them was assigned using analytic hierarchy process. Weighted Sum Overlay (WSO) analyses of ARC GIS software was employed to produce flood vulnerability map. Then, the accuracy of generated flood risk map was validated using historical flood data. According to the result, about 3.08%, 14.62% and 20.66% of Shewa Robit town are at a very high, high and moderate flash flood risk, respectively. In addition to this, flood risk was also quantified in terms of land use land cover. The result indicates that the settlement land use is the most vulnerable with an estimated area of 12.01 ha, 99.57 ha and 174.16 ha in very high, high and moderate risk classes. The outcome of the study will be applicable in flood hazard management and mitigation strategies.

Estimation of the 10-Year Risk of Cardiovascular Diseases: Using the SCORE, WHO/ISH, and Framingham Models in the Shahrekord Cohort Study in Southwestern Iran.

Background: Predicting the risk of cardiovascular diseases (CVDs) helps the management of high-risk individuals by the health system. We sought to determine the 10-year risk of CVDs in the Shahrekord Cohort Study (SCS). Methods: In this cross-sectional study based on the SCS in the southwest of Iran, the demographic, anthropometric, clinical, and laboratory data of 5152 persons recruited in the SCS by census method from 2016 to 2017 were used. R software was utilized to calculate the 10-year risk of CVDs according to the World Health Organization/International Society of Hypertension (WHO/ISH) chart, the Framingham Risk Score (FRS) model, and the Systematic Coronary Risk Evaluation (SCORE) model. Results: The mean age of the participants was 49.49±9.40 years, and 50.3% of them were female. According to the WHO/ISH chart, 94.1% of the participants were in the low-risk class, 4.1% in the moderate-risk class, and 0.4% in the high-risk class. Based on the FRS model, 72.2% of the participants were in the low-risk class, 18% in the middle-risk class, and 9.8% in the high-risk class. On the basis of the SCORE model for low-risk areas, 55.3% of the participants were in the low-risk class, 39.6% in the moderate-risk class, and 5.1% in the high-risk class. The agreement concerning risk estimation between the models was approximately 70%. Conclusion: The risk estimated in this study was higher than that in other similar studies. For monitoring risk trends over time, it is essential to nativize a valid risk function, including ethnicity and geographical characteristics, for the Iranian population.

Creating HIV risk profiles for men in South Africa: a latent class approach using cross-sectional survey data.

IntroductionEngaging at‐risk men in HIV prevention programs and services is a current priority, yet there are few effective ways to identify which men are at highest risk or how to best reach them. In this study we generated multi‐factor profiles of HIV acquisition/transmission risk for men in Durban, South Africa, to help inform targeted programming and service delivery.MethodsData come from surveys with 947 men ages 20 to 40 conducted in two informal settlements from May to September 2017. Using latent class analysis (LCA), which detects a small set of underlying groups based on multiple dimensions, we identified classes based on nine HIV risk factors and socio‐demographic characteristics. We then compared HIV service use between the classes.ResultsWe identified four latent classes, with good model fit statistics. The older high‐risk class (20% of the sample; mean age 36) were more likely married/cohabiting and employed, with multiple sexual partners, substantial age‐disparity with partners (eight years younger on‐average), transactional relationships (including more resource‐intensive forms like paying for partner’s rent), and hazardous drinking. The younger high‐risk class (24%; mean age 27) were likely unmarried and employed, with the highest probability of multiple partners in the last year (including 42% with 5+ partners), transactional relationships (less resource‐intensive, e.g., clothes/transportation), hazardous drinking, and inequitable gender views. The younger moderate‐risk class (36%; mean age 23) were most likely unmarried, unemployed technical college/university students/graduates. They had a relatively high probability of multiple partners and transactional relationships (less resource‐intensive), and moderate hazardous drinking. Finally, the older low‐risk class (20%; mean age 29) were more likely married/cohabiting, employed, and highly gender‐equitable, with few partners and limited transactional relationships. Circumcision (status) was higher among the younger moderate‐risk class than either high‐risk class (p < 0.001). HIV testing and treatment literacy score were suboptimal and did not differ across classes.ConclusionsDistinct HIV risk profiles among men were identified. Interventions should focus on reaching the highest‐risk profiles who, despite their elevated risk, were less or no more likely than the lower‐risk to use HIV services. By enabling a more synergistic understanding of subgroups, LCA has potential to enable more strategic, data‐driven programming and evaluation.

Modeling and mapping forest fire risk in the region of Aures (Algeria)

The objective of this study is to modeling and mapping the Forest fire risk in the region of Aures situated in Northeast of Algeria, through the application of multi-criteria analysis methods to integrate geographic information systems (GIS) and remote sensing. The methodology is based on a weighted linear combination of three parameters that influence the initiation and propagation of a forest fire. These are vegetation, topography and anthropogenic index. The result is a vulnerability map classified into four classes according to pixel values. very high risk class forms 18,28% of the study area, high risk class forms 42,42%, moderate risk class forms 5,24% and 34,05% of the area is low risk.

Physical Disorders are Associated with Health Risk Behaviors in Chinese Adolescents: A Latent Class Analysis.

It is known that health risk behaviors (HRBs) can lead to a variety of physical and mental health problems among adolescents, but few studies have paid attention to the relationship between latent classes of HRBs and adolescent diseases. The purpose of this study was to use latent class analysis (LCA) to clarify the potential subgroups of HRBs (smoking, drinking, screen time, non-suicidal self-injuries, suicidal behaviors, and unintentional injuries) and examine the association between the subgroups of HRBs and physical disorders (diarrhea, fever, cough, and vomiting) with multiple logistic regression analysis, in Chinese adolescents. Self-reported HRBs and physical disorders were used to evaluate 22,628 middle school students in six cities of China, from November 2015 to January 2016, based on a multistage stratified cluster sampling approach. The prevalence of diarrhea, fever, cough, and vomiting was 23.5%, 15.9%, 50.6%, and 10.7%, respectively. We identified four latent classes of HRBs by LCA, including low-risk class, moderate-risk class 1 (smoking, drinking, and screen time), moderate-risk class 2 (non-suicidal self-injuries and suicidal behaviors, unintentional injuries), and high-risk class (smoking, drinking, screen time, non-suicidal self-injuries, suicidal behaviors, and unintentional injuries), which were 64.0%, 4.5%, 28.8% and 2.7% of participants, respectively. Compared to the low-risk class, all other classes showed higher risk for these physical disorders (P < 0.01 for each). In particular, the high-risk class had the highest risk (diarrhea (odds ratio (OR) = 2.628, 95% confidence interval (CI) 2.219 to 3.113), fever (OR = 3.103, 95% CI 2.591 to 3.717), cough (OR = 2.142, 95% CI 1.805 to 2.541), and vomiting (OR = 3.738, 95% CI 3.081 to 4.536). In conclusion, these results indicated that heterogeneity exists in HRBs, and subgroups of HRBs were correlated to the occurrence of common physical disorders in Chinese adolescents. Therefore, multiple HRBs rather than single factors should be considered for the prevention of common physical disorders in schools.