Path Analysis on the Biopsychosocial Determinants of Type 2 Diabetes Mellitus and Depression at Dr. Moewardi Hospital, Surakarta

Background: Diabetes Mellitus (DM) is a a major disease that is threatening global population health. This disease ranks third by global public health priority. The incidence of type 2 DM in 2014 was 442 million patients worldwide. Indonesia is one of 10 countries with high DM incidence. The incidence of type 2 DM in Indonesia in 2014 was 10 million patients. This study aimed to examine the biopsychosocial determinants of type 2 Diabetes Melitus and depression at Dr. Moewardi Hospital, Surakarta, using path analysis.Subjects and Method: This was an analytic and observational study with case control design. The study was conducted at Dr. Moewardi Hospital, Surakarta, from August to October, 2017. Sample consisting of 100 patients type 2 DM and 100 non DM patients were selected for this study by fixed disease sampling. The dependent variable was type 2 DM. The independent variables were body age, mass index, education level, occupation, stres, family income, comorbidity, activity, and family history of type 2 DM. The data were collected using medical record and questionnaire. The data were analyzed by path analysis.Results: The risk of type 2 DM increased with higher body mass index (b= 2.66; 95% CI= 1.41 to 3.91; p<0.001), higher income (b=-0.93; 95% CI= -1.90 to 0.045; p=0.062), older age (b= 2.88; 95% CI= 0.62 to 5.15; p= 0.013), presence of DM family history (b= 2.56; 95% CI= 1.45 to 3.68; p <0.001), and comorbidity (b= 3.25; 95% CI= 2.07 to 4.43; p<0.001). The risk of depression increased by type 2 DM (b= 1.032; 95% CI= 0.42 to 1.63; p= 0.001). Body mass index increased with higher physical activity (b= -1.41; 95% CI= -2.03 to -0.79; p<0.001). Income increased with high education level (b= 2.58; 95% CI= 1.83 to 3.33; p<0.001). High physical activity increased with occupation (b=0.96; 95% CI= 0.38 to 1.53;p= 0.001).Conclusion: The risk of type 2 DM increased with higher body mass index, higher income, older age, presence of DM family history, and comorbidity.Keyword: biopsychosocial determinants, type 2 DM, depressionCorrespondence: Esty Budiarti. Masters Program in Public Health, Universitas Sebelas Maret, Jl. Ir. Sutami 36 A, Surakarta 57126, Central Java. Email:[email protected] of Epidemiology and Public Health (2018), 3(1): 1-14https://doi.org/10.26911/jepublichealth.2018.03.01.0

Factors Affecting the Occurrence of Type 2 Diabetes Mellitus and Depression: A New Evidence Using a Path Model Approach

Background: Type 2 Diabetes Mellitus (Type 2DM) ranks third by global public health priority. Globally, the incidence of type 2 DM in 2014 was 442 million patients. Indonesia is one of 10 countries with high DM incidence. In 2014 the incidence was 10 million patients. Type 2 DM is one of the most psychologically demanding chronic medical illness in adult. Comorbidity between diabetes and depression is quite common. However, limited data exists to document biopsychosocial predictors of depressive symptoms in Indonesian patients. This study aimed to examine the biopsychosocial factors affecting the occurence of type 2 DM and depression at Dr. Moewardi Hospital, Surakarta, using path analysis. Subjects and Method: This was case control study conducted at Dr. Moewardi Hospital, Surakarta, from August to October 2017. Sample consisting of 100 patients type 2 DM and 100 non DM patients were selected for this study by fixed disease sampling. The dependent variable was type 2 DM. The independent variables were body age, mass index, education level, occupation, stres, family income, comorbidity, activity, and family history of type 2 DM. The data were collected using medical record and questionnaire. The data were analyzed by path analysis. Results: The biopsychosocial factors that directly affected the occurence of type 2 DM and indirectly affected the occurrence of depression were highbody mass index (b= 2.66; 95% CI= 1.41 to 3.91; p<0.001), high income (b= -0.93; 95% CI= -1.90 to 0.045; p= 0.062), older age (b= 2.88; 95% CI= 0.62 to 5.15; p=0.013), presence of DM family history (b= 2.56; 95% CI= 1.45 to 3.68; p<0.001), and comorbidity (b= 3.25; 95% CI= 2.07 to 4.43; p<0.001). The occurrence of type 2 DM and depression was indirectly affected by physical activity, education level, physical activity, and occupation. Conclusion: Higher body mass index, higher income, older age, presence of DM family history, and comorbidity, are the factors that increase the occurrence of type 2 DM and depression. Keywords: biopsychosocial factors, type 2 DM, depression, path analysi

Environmental changes and violent conflict

This letter reviews the scientific literature on whether and how environmental changes affect the risk of violent conflict. The available evidence from qualitative case studies indicates that environmental stress can contribute to violent conflict in some specific cases. Results from quantitative large-N studies, however, strongly suggest that we should be careful in drawing general conclusions. Those large-N studies that we regard as the most sophisticated ones obtain results that are not robust to alternative model specifications and, thus, have been debated. This suggests that environmental changes may, under specific circumstances, increase the risk of violent conflict, but not necessarily in a systematic way and unconditionally. Hence there is, to date, no scientific consensus on the impact of environmental changes on violent conflict. This letter also highlights the most important challenges for further research on the subject. One of the key issues is that the effects of environmental changes on violent conflict are likely to be contingent on a set of economic and political conditions that determine adaptation capacity. In the authors' view, the most important indirect effects are likely to lead from environmental changes via economic performance and migration to violent conflict. © 2012 IOP Publishing Ltd

Introducing SpatialGridBuilder: A new system for creating geo-coded datasets

Researchers in the conflict research community have become increasingly aware that we can no longer depend on state-aggregated data. Numerous factors at the substate level affect the nature of human interactions, so if we really want to understand conflict, we need to find more appropriate units of analysis. However, while many conflict researchers have realized this, actually taking the next step and performing data analysis on spatial data grids has remained a rather elusive goal for many because of the difficulty of learning the new techniques to perform such analyses. This paper introduces SpatialGridBuilder, a new, freely available, open-source system with the goal of empowering conflict researchers with no background in GIS methods to start their own spatial analyses. SpatialGridBuilder allows the researcher to: (a) create entirely new spatial datasets, based on the needs of their own research; (b) import their own spatial data; (c) easily add a range of important variables to the datasets, including commonly used conflict variables, plus new variables that have not been presented before; and (d) visualize graphical renderings of this data. Having done this, SpatialGridBuilder will then export the dataset for the researcher to analyse using conventional statistical methods. This article introduces the new program, and demonstrates how it can be used to set up such a statistical analysis. It also shows how different results can be achieved by building grids of different resolutions, thereby encouraging researchers to choose grid resolutions appropriate to their research questions and data. The article also introduces a novel means of determining infrastructure complexity, using Google maps

Driving pro-environmental change in tourist destinations: encouraging sustainable travel in National Parks via partnership project creation and implementation

© 2016 Taylor & Francis. This paper explores a key challenge in introducing more sustainable transport practices at destinations: achieving modal shift in visitor travel from cars to physically active or public transport to reduce tourism's environmental impacts. It centres on using partnership led projects bringing together the many public and private sector organisations involved, to drive destination change and development. To date, research has centred on pro-environmental change for individuals and individual organisations: little is known about the mechanisms of pro-environmental change via complex multi-partner organisations. The paper reports research into the processes involved in successful projects to provide alternatives to car travel in three UK National Parks by using partnerships to obtain funding and implement change. Based on case studies informed by in-depth interviews with key stakeholders involved in pro-environmental change implementation, narratives are analysed to explain the change process, and mapped against existing literature and theories of change. Conclusions show the role of inspired individuals, supportive senior management, strong governance, better visitor experiences and, most significantly, communication and communication of the benefits of change to stakeholders. The research suggests why and how change occurs in partnerships, contributes to better theories of change and offers guidance on understanding and implementing change processes worldwide

On the Interplay between Resource Extraction and Polluting Emissions in Oligopoly

This paper offers an overview of the literature discussing oligopoly games in which polluti ng emissions are generated by the supply of goods requiring a natural resource as an input. An analytical summary of the main features of the interplay between pollution and resource extraction is then given using a differential game based on the Cournot oligopoly model, in which (i) the bearings on resource preservation of Pigouvian tax rate tailored on emissions are singled out and (ii) the issue of the optimal number of firms in the commons is also addressed

Future Imaginings: Organizing in Response to Climate Change

Climate change has rapidly emerged as a major threat to our future. Indeed the increasingly dire projections of increasing global average temperatures and escalating extreme weather events highlight the existential challenge that climate change presents for humanity. In this editorial article we outline how climate change not only presents real, physical threats but also challenges the way we conceive of the broader economic, political and social order. We asked ourselves (and the contributors to this special issue) how we can imagine alternatives to our current path of ever escalating greenhouse gas emissions and economic growth. Through reference to the contributions that make up this special issue, we suggest that critically engaging with the concept of social, economic and political imaginaries can assist in tackling the conceptual and organizational challenges climate change poses. Only by questioning current sanitised and market-oriented interpretations of the environment, and embracing the catharsis and loss that climate change will bring, can we open up space for new future imaginings

KLASIFIKASI HABITAT PERAIRAN DANGKAL DARI CITRA MULTISPASIAL DI PERAIRAN PULAU KAPOTA DAN PULAU KOMPOONE, KEPULAUAN WAKATOBI

Habitat perairan dangkal sangat penting dipetakan diantaranya karena: (1) mendukung perencanaan, manajemen, dan pengambilan keputusan tata ruang pemerintah; (2) mendukung dan mendesain Marine Protected Area (MPA); (3) melakukan program penelitian ilmiah yang bertujuan untuk menghasilkan pengetahuan tentang ekosistem bentik dan geologi dasar laut; (4) melakukan penilaian sumber daya dasar laut yang hidup dan tidak hidup untuk tujuan ekonomi dan menajemen, termasuk rancangan cadangan perikanan. Hingga saat ini belum ada standar untuk tingkat kedetailan peta tematik ekosistem pesisir khususnya habitat perairan dangkal sesuai kebutuhan pengelolaan wilayah pesisir dengan skema klasifikasi tertentu. Penelitian ini bertujuan untuk membandingkan akurasi peta hasil klasifikasi habitat perairan dangkal antara citra SPOT 6, Sentinel 2A, dan Landsat 8 menggunakan algoritma klasifikasi support vector machine. Lokasi penelitian terletak di Kepulauan Wakatobi, meliputi 2 lokasi yaitu Pulau Kapota dan Pulau Kompoone. Pengambilan data in-situ dilaksanakan pada tanggal 7-11 Juli 2019. Sebanyak 347 ground truth dan foto transek hasil sampling di lapangan telah dianalisis menggunakan coral point count with excel extension (CPCe). Skema klasifikasi yang dihasilkan yaitu 8 kelas habitat bentik, selanjutnya dilakukan klasifikasi dengan mengkelaskan kembali menjadi 6 dan 5 kelas. Hasil yang diperoleh pada citra SPOT-6 untuk semua kelas habitat perairan dangkal yang digunakan memiliki overall accuracy yang lebih besar. Perbedaan ukuran piksel (resolusi spasial) dan jumlah skema klasifikasi sangat memengaruhi hasil akurasi.Shallow water habitat mapping is important to do because: (1) it can support the planning, management, and decision making of government spatial; (2) it can support and design a Marine Protected Area (MPA); (3) it can conduct a scientific research program to determine a knowledge about benthic ecosystem and seabed geology; (4) it can do seabed resource valuation, both biotic and abiotic, for economic and management goals. Nowadays, the standardization of thematic map details level in coastal ecosystem has not determined, especially in shallow water habitat based on coastal management needs in certain scale. The study aims to compare map accuracy level between SPOT 6, Sentinel 2A, and Landsat 8 classification results using support vector machine algorithm. The study site is in Wakatobi Island, including Kapota Island and Kompoone Island. The in-situ data took on July 2019. The 347 ground truth and transect images in the field analyzed using Coral Point Count with Excel Extension (CPCe). The classification scheme that was gotten is 8 habitat benthic classes, then conducted classification with classify them to be 6 and 5 classes. The result from SPOT 6 for 5 habitat classes has the highest overall accuracy. The differences between pixel (spatial resolution) and the amount of classification scheme influence accuracy results

Which Green Matters for Whom? Greening and Firm Performance across Age and Size Distribution of Firms.

A growing body of literature links firm performance with sustainability efforts.We contribute to this literature by developing a novel framework for contextualising greening through the lens of tangibility and visibility of greening activities and examine the impact of different types of greening on firm performance along the age and size distribution of firms. The empirical results based on a large-scale database suggest that rewards to different types of greening differ across age and size distributions