Objectives: Community-Based Participatory Research (CBPR) is a kind of health promotion approach to increase social cohesion and sense of community, which has built the collaborated partnership in all phases. This has the co-ownership of research objectives and knowledges produced by residents, and the outcome was taken to enhance community empowerment. This study performed to embody CBPR, which had regulated collective health status approached by social epidemiology. Methods: Reference review had been exercised focused on CBPR books and papers published since 1990. Our interests were aimed at its paradigm and methodological issues. Particularly, we problematized its feasibility in the social and behavioral foundations of pubic health. Results: According to the review, CBPR shared critical understanding and decision-making related to their community development including health status. Therefore, it was strength-based approach in spite of scientific dichotomy. CBPR created social cohesion and community empowerment with all participants, because it sublated contradiction between subjectivism and objectivism. Conclusions: The success of CBPR needs what we so called trust, democracy, collaboration, devotion, and consensus of equity. Despite these factors, CBPR may be a methodological transition to prepare some intervention of health inequality. This is because it does emphasize a mixture of theory and praxis to manage vulnerable people in community.
Shin, Mi Na;Lee, Kyung Hea;Lee, Hye Sang;Sasaki, Satoshi;Oh, Hea Young;Lyu, Eun Soon;Kim, Mi Kyung
Nutrition Research and Practice
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제7권5호
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pp.400-408
/
2013
Obesity may be the consequence of various environmental or genetic factors, which may be highly correlated with each other. We aimed to examine whether grandmaternal and maternal obesity and environmental risk factors are related to obesity in daughters. Daughters (n = 182) recruited from female students, their mothers (n = 147) and their grandmothers (n = 67) were included in this study. Multivariable logistic regression was used to analyze the association between the daughter's obesity and maternal, grandmaternal, and environmental factors. Maternal heights of 161-175cm (OD: 8.48, 95% CI: 3.61-19.93) and 156-160 cm (2.37, 1.14-4.91) showed positive associations with a higher height of daughter, compared to those of 149-155 cm. Mothers receiving a university or a higher education had a significant OR (3.82, 1.27-11.50) for a higher height of daughter compared to those having a low education (elementary school). Mother having the heaviest weight at current time (59-80 kg, 3.78, 1.73-8.28) and the heaviest weight at 20 years of age (51-65 kg, 3.17, 1.53-6.55) had significant associations with a higher height of daughters, compared to those having the lightest weight at the same times. There was no association between the height, weight, and BMI of daughters and the characteristics and education of her grandmothers. In conclusion, although genetic factors appear to influence the daughter's height more than environmental factors, the daughter's weight appears to be more strongly associated with individual factors than the genetic factors.
Kasaeian, Amir;Mosavi-Jarrahi, Alireza;Abadi, Alireza;Mahmoodi, Mahmood;Mehrabi, Yadollah;Mohammad, Kazem;Eshraghian, Mohammad Reza;Zare, Ali
Asian Pacific Journal of Cancer Prevention
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제16권14호
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pp.5853-5858
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2015
Background: The survival rate reflecting prognosis of breast cancer patients is usually estimated based on crude survival methods such as observed and cause-specific. In situations where data are based on population-cancer registries, this method may produce biased estimations. This study therefore aimed to estimate the net survival of breast cancer based on relative survival. Materials and Methods: Data for 622 breast cancer patients diagnosed at the Iran Cancer Institute during 1990-95 and tracked till the end of 2000 were analyzed. For estimation of relative survival, Ederer's second method and SAS (9.1) and STATA (11) software were used. Results: Threeyear relative survivals of 85%, 90%, 80% and 67% were observed for age groups 15-44, 55-59, 60-74, and 75+years-old, respectively. A relative survival of approximately one was observed for two subsequent years for age-group 45-59 years-old. A value greater than one for two subsequent years of follow-up was observed in the age-group 60-74 years-old. Conclusions: Tracking the diagnosis of breast cancer, the relative survival decreases as we go to higher age-groups. It is also perceived that through follow-up, relative survival first decreased and then increased a little. The statistical cure point is acceptable for age group 45-59 years-old while for age-groups 15-44 and 60-74 years old is a sign of low quality data for some follow-up intervals.
Background: Starting from March 2020 until December 2021, different phases of Covid-19 pandemic have been identified in Italy, with several containing/lifting measures progressively enforced by the National government. In the present study, we investigate the change in occupational risk during the subsequent pandemic phases and we propose an estimate of the incidence of the cases by economic sector, based on the analysis of insurance claims for compensation for Covid-19. Methods: Covid-19 epidemiological data available for the general population and injury claims of workers covered by the Italian public insurance system in 2020-2021 were analyzed. Monthly Incidence Rate of Covid-19 compensation claims per 100,000 workers (MIRw) was calculated by the economic sector and compared with the same indicator for general population in different pandemic periods. Results: The distribution of Covid-19 MIRw by sector significantly changed during the pandemic related to both the strength of different waves and the mitigation/lifting strategies enforced. The level of occupational fraction was very high at the beginning phase of the pandemic, decreasing to 5% at the end of 2021. Healthcare and related services were continuously hit but the incidence was significantly decreasing in 2021 in all sectors, except for postal and courier activities in transportation and storage enterprises. Conclusion: The analysis of compensation claim data allowed to identify time trends for infection risk in different working sectors. The claim rates were highest for human health and social work activities but the distribution of risk among sectors was clearly influenced by the different stages of the pandemic.
Objectives: This study was to examine the association between structural and functional characteristics of social network and self-rated health in middle-aged Korea population. We also explored gender difference in the relationship between social network and health. Methods: Data were collected from individuals aged 40-69 years old participating in the 2005 survey for the Korean Genome & Epidemiology Study. We examined the association between social network, social support, social conflict and self-rated health using multiple logistic regression analysis stratified by gender. Results: The extent and contact frequency of close people, and social participations were associated by not only the positive function but also the negative function of social network. Both the positive and negative functions of social network affected self-rated health. The relationship between the function of social network and health showed a gender difference: only positive function was significantly associated with health in men while only negative function had significant relationship with health in women. Conclusions: Social support and social conflict affected the health in both genders through different ways. The ambivalent effect of social network on health should be explored further.
Violanti, John M.;Charles, Luenda E.;Gu, Ja K.;Burchfiel, Cecil M.;Andrew, Michael E.;Joseph, Parveen N.;Dorn, Joan M.
Safety and Health at Work
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제4권1호
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pp.27-36
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2013
Objectives: Mental health has been shown to be linked with certain underlying physiological mechanisms. The objective of this cross sectional study was to investigate the relationship between depressive symptoms and brachial artery reactivity (BAR) in an understudied population: police officers. Methods: Participants were 351 police officers who were clinically examined in the Buffalo Cardio-Metabolic Police Stress (BCOPS) study. BAR was performed using standard B-Mode ultrasound procedures. Depressive symptoms were measured using the Center for Epidemiological Studies Depression (CES-D) scale. Mean values of the difference between the baseline and maximum diameters of the brachial artery were determined across three categories of CES-D score using the analysis of variance and the analysis of covariance. p-values for linear trends were obtained from linear regression models. Results: The mean age (${\pm}$ standard deviation) of all officers was $40.9{\pm}7.2$ years. Women had a slightly higher mean CES-D score than men ($8.9{\pm}8.9$ vs. $7.4{\pm}6.4$) and a slightly higher percentage increase of BAR than men (6.90 vs. 5.26%). Smoking status significantly modified the associations between depressive symptoms and BAR. Among current smokers, mean absolute values of BAR significantly decreased as depressive symptoms increased after adjustment for age, gender, race/ethnicity, hypertension, and diabetes; the multivariate-adjusted p-values were 0.033 (absolute) and 0.040 (%). Associations between depressive symptoms and BAR were not statistically significant among former smokers or never smokers. Conclusion: Depressive symptoms were inversely associated with BAR among police officers who were current smokers and together may be considered a risk factor for cardiovascular disease among police officers. Further prospective research is warranted.
Park, Hyeoun-Ae;Jung, Hyesil;On, Jeongah;Park, Seul Ki;Kang, Hannah
Healthcare Informatics Research
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제24권4호
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pp.253-262
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2018
Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.
Background The coronavirus disease 2019 (COVID-19) outbreak has had a major impact worldwide. Several countries have implemented restrictions on social interaction ("social distancing"). Several studies have reported that the epidemiology of trauma patients, such as those with facial bone fractures, has changed after COVID-19 pandemic. This study aimed to further explore these specific changes. Methods This was a retrospective study of patients who presented to a single institution with facial bone fractures between January 1, 2016, and December 31, 2020. Baseline patient demographics, clinical information, type of fracture, etiology, and operative management were compared before and after COVID-19. Results Of all cases, 3,409 occurred before COVID-19, and 602 occurred after COVID-19. Since the outbreak of COVID-19, the number of patients with facial fractures has not decreased significantly. A significant increase was noted in fractures that occurred outdoors (p < 0.001). However, a decrease was observed in operative management between the groups (p < 0.001). There was no significant difference in the proportion of assault, fall-down, industrial accident, or roll-down. In contrast, the proportion of traffic accidents and slip-down categories increased significantly (p < 0.05). Moreover, a significant decrease was found in the proportion of the sports category (p = 0.001) Conclusions It was confirmed through this study that COVID-19 pandemic also affected epidemiology of facial fractures. Focusing on these changes, it is necessary to develop safety measures to reduce facial fractures.
Objectives: The present study examined relationships between socioeconomic status (SES) and obesity and body mass index (BMI) as well as the effects of health-related behavioral and psychological factors on the relationships. Methods: A cross-sectional population-based study was conducted on Korean adults aged 20 to 79 years using data from the 2001, 2005, and 2007 to 2009 Korea National Health and Nutrition Examination Survey. Multivariate logistic and linear regression models were used to estimate odds ratios of obesity and mean differences in BMI, respectively, across SES levels after controlling for health-related behavioral and psychological factors. Results: We observed significant gender-specific relationships of SES with obesity and BMI after adjusting for all covariates. In men, income, but not education, showed a slightly positive association with BMI (p<0.05 in 2001 and 2005). In women, education, but not income, was inversely associated with both obesity and BMI (p<0.0001 in all datasets). These relationships were attenuated with adjusting for health-related behavioral factors, not for psychological factors. Conclusions: Results confirmed gender-specific disparities in the associations of SES with obesity and BMI among adult Korean population. Focusing on intervention for health-related behaviors may be effective to reduce social inequalities in obesity.
Khan, Hafiz Mohammad Rafiqullah;Saxena, Anshul;Gabbidon, Kemesha;Rana, Sagar;Ahmed, Nasar Uddin
Asian Pacific Journal of Cancer Prevention
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제15권6호
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pp.2893-2900
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2014
Background: Statistical methods are very important to precisely measure breast cancer patient survival times for healthcare management. Previous studies considered basic statistics to measure survival times without incorporating statistical modeling strategies. The objective of this study was to develop a data-based statistical probability model from the female breast cancer patients' survival times by using the Bayesian approach to predict future inferences of survival times. Materials and Methods: A random sample of 500 female patients was selected from the Surveillance Epidemiology and End Results cancer registry database. For goodness of fit, the standard model building criteria were used. The Bayesian approach is used to obtain the predictive survival times from the data-based Exponentiated Exponential Model. Markov Chain Monte Carlo method was used to obtain the summary results for predictive inference. Results: The highest number of female breast cancer patients was found in California and the lowest in New Mexico. The majority of them were married. The mean (SD) age at diagnosis (in years) was 60.92 (14.92). The mean (SD) survival time (in months) for female patients was 90.33 (83.10). The Exponentiated Exponential Model found better fits for the female survival times compared to the Exponentiated Weibull Model. The Bayesian method is used to obtain predictive inference for future survival times. Conclusions: The findings with the proposed modeling strategy will assist healthcare researchers and providers to precisely predict future survival estimates as the recent growing challenges of analyzing healthcare data have created new demand for model-based survival estimates. The application of Bayesian will produce precise estimates of future survival times.
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