John Robert Medina

[John Robert Medina]

1. Most epidemiologists are focused on doing observational and experimental studies. There can only be a few who are interested in doing ecologic studies. This can one possible reason. Another is there are only few researchers who are trained in spatial statistics. Most of the statistical tests that are being used in the analysis part of epidemiologic studies are grounded on classical statistical theories that always follow the assumption of independence of observations. Location is seldom taken into account/
Spatial epidemiology is an interdisciplinary science because it utilizes techniques and methods from other discipline such as cartography, statistics, epidemiology, public health, sociology, etc.

2. In psychology, we often say that human development is a product of both nature and nurture. It is not only the biological and genetic make-up of an individual that can influence a person’s growth and development, but also the biopsychosocial environment. In some twin studies, twins who were raised separately can developed differently and can have dissimilar attributes, despite the similarity in their genetic make-up. Some workers are more predispose to be infected with a certain disease. Say for example, fishermen who are catching fishes in rivers with infected snails are more prone to schistosomiasis than fishermen in the seas. Goiter is more common among people living in mountain regions than those who are living near the seas.

[John Robert Medina]

I would like to ask for a clarification. Based on my understanding of what was written in the paper, provincial data in 2011 was used. I am not certain if what the author had at hand was individual level data or an aggregated data per province. Because if it is aggregated data per province, the study design is not cross-sectional design but ecologic study design instead.

[John Robert Medina]

1. Why was the author interested in investigating the suicide problem in Thailand during the time?

Aside from the continued increase of suicide rates over the past decade, studying the influence of economic and social factors on suicide rates had caught the interest of scholars. In addition, there is paucity of local literatures that investigated suicide in Thailand. Given that Thailand has a different context from developed countries, where there are many published studies on suicides, this reason, along with the aforementioned reasons, prompted the author to investigate the suicide problem.

2. Each of students picks one potential risk factor mentioned in the paper and explains how the variable can contribute to the suicide rate?
Regression analysis showed that income is a significant regressor in the first model. In the first model, 60.9% of the variability of the regressand is attributable to the included independent variables. Controlling for the effects of other independent variables, suicide rate increases by 0.010 unit for every unit increase in income.

3. How statistical modeling can contribute to investigate the epidemiology and spatial aspects of Thai suicide problem?
Statistical modelling allows us to understand how social and economic factors drove the variation in our outcome of interest, which is Thai suicide problem. Hence, we obtain which of the many factors tends to affect the latter more within some degree of certainty.

[John Robert Medina]

1. What are possible reasons locations in epidemiological research have not been incorporated as much as other components in epidemiological research? How can spatial epidemiology be considered as an interdisciplinary science?

One of the possible reason is the lack of expertise in some LMICs. Most of the epidemiologists in LMICs are not trained in geographical or spatial epidemiology. Another possible reason is the lack of opportunity to be trained in spatial epidemiology. In my country, there are only two master’s program on epidemiology. One is public health epidemiology, and the other is clinical epidemiology. None of the two programs are offering courses on spatial epidemiology so it necessitated me to enroll in this course so I can have at least a formal course with credit on spatial epidemiology. Even if we have collected complete data with spatial information and stored in our public health databases, if we do not have the expertise, we will not be able to produce any quality output. There could be very few researchers in our country who are working on spatial epidemiological projects, but most of us did not attend any formal course. We just received training on how to create maps in GIS (ArcGIS, QGIS) using point and areal data and attended short trainings or research internship on spatial epidemiology.

Spatial epidemiology is an interdisciplinary science because it entails expertise from different fields such as geography, social science, public health, epidemiology, biostatistics, etc. The mere fact that experts of different fields collaborate on a spatial epidemiological project, it is already a reflection that spatial epidemiology is interdisciplinary. Moreover, some who are working on spatial epidemiological projects are formally trained not specifically on the field of epidemiology but other field such as statistic, geography, etc.

2. Explain why it is widely recognized that the place where an individual lives or works should be considered as a potential disease determinant and give some examples?

I would like to quote Tobler’s First Law of Geography, which states that “everything is related to everything else, but near things are more related than distant things”. When the atomic bomb was dropped in Hiroshima during the World War II. Those who are living nearby had suffered from the immediate effect of the radiation. Those who lived and were spared from the immediate effect of radiation were followed through. Later on they developed the long term effect of radiation such as the development of cancers. People who were living several miles away from Hiroshima were spared not only from the immediate but also from the long-term sequelae of radiation. From this example, we can see how location can be a determinant of disease occurrence.

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