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HOW TO WRITE DESCRIPTION OF STUDY AREA IN RESEARCH

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DESCRIPTION OF THE STUDY AREA

Description of the study area is the act of describing the characteristics, qualities and physical features of an area, location, neighbourhood, city or community that is being studied or investigated for research purposes. Describing a study area is an important part of research, not just to the researcher, but to all concerned both now and in the future.

The study area is sometimes referred to as a study site in research, some higher institutions refer to the description of the study area as the “ profile of the study area “. To properly give a detailed description of an area, the researcher should have an in-depth knowledge of the study area in the project , and this can only be possible by reviewing other related materials in the form of published Journals, textbooks, etc., by academicians within a particular field of study or when the researcher is familiar with the neighbourhood or area in question.

In a dissertation, the description of a study area usually comes under Chapter Three (in most cases) except in some institutions with special formats for presenting research papers. But the key point is that the captions on whichever chapter this subject is mentioned are usually written as “A Brief Description of Study Area” . This is not to limit the information provided but to apply some sort of concision in that it should be skillfully couched to enable a good flow in the presentation without creating confusion.

In summary, there are three aspects to the description of study area – (brief) (description) (study area)

The fact that it is termed brief does not necessarily mean it shouldn’t be detailed.

Your description should cover a broad spectrum of information; this would include location, geography, climatic condition, social infrastructure, vegetation, density, humidity, temperature, topography, terrain and so on.

The study area should be your area of coverage that is, your case study. Introducing information from other areas or regions will have no significance on the subject matter, hence your primary focus would be on the area your research is covering. At this point, you are expected to include maps of the study area (in colour).

What you’re expected to write is a detailed description of your study area to give your reader an idea of what your study area looks like. Get Samples

Depending on the research topic, the pattern of describing the study area could vary;

If a project topic is focused on investigating issues or problems that concern a state or province the description will bother around everything that makes up the location. For example “ Evaluation of the Issues Affecting Girl-Child Education in FCT Abuja ” is a broad topic that focuses on FCT-Abuja as a case study, hence to describe the study area which in this case is FCT-Abuja, adequate data on everything that makes up or best describes Abuja as a Federal Capital Territory has to be brought in and properly described. The description should include the vegetation in Abuja, the population of Abuja, Abuja’s topography, its climatic condition, the culture of people living in Abuja, the terrain (that is, the flatness or sloppiness of Roads in Abuja), the nature of business, market data, rainfall, electricity, common food, the number of ethnic group in the territory, religion of residents among others.

The essence of the description of the study area is to enable an outsider to have an idea of the area or neighbourhood that is being researched, this knowledge will also help the readers to understand the body of your work and try to envision what your study is trying to pass across. It will also influence people’s judgment of the topic being researched.

If the project topic is centred on a particular catchment or neighbourhood for example “ A Critical Examination of Facilities Management Strategy on Public Properties – A Case Study of Central Bank of Nigeria Staff Quarters ” the description will take a different shape. In this case, it should include a brief summary of the neighborhood where the CBN staff quarters are located followed by a broad description of the CBN staff quarters environment and premises. Let’s look at the following example;

“ The CBN staff quarters is a large purpose-built residential estate for senior, intermediate and junior CBN staff members. It is properly fenced around its perimeter solid block walls with a giant double two-way gate at the main entrance and another small pedestrian gate by the side. The estate comprises of the following; 16 Blocks of 8 units of 2bedroom flats each totalling 128 flats, 12 Block of 8 units of 3bedroom flats each totalling another 97 flats, and 6 Blocks of 6 units of 3bedroom flats each totalling 36 flats with additional buildings at the rear for intermediate and junior staff. The senior staff also have a large garage for parking vehicles .”

In addition, a detailed description of the site and construction details of the buildings will beef up your work. For example:

“ The site is rectangular, it has a flat or table surface and properly drains off water during heavy downpours. The site measures approximately 22.32 hectares .”

The construction details should encompass; the type of floor, wall, doors, windows, ceiling, fittings, roof and the materials used in constructing them. For example, a brief description of the floor can be written like this “ The floor is made of mass concrete on hardcore filling well rammed over consolidated laterite and finished with terrazzo material ” The other building components (windows, doors, ceiling, wall, fitting and roof) should have their description proper done like the “floor”.

The facilities in the CBN staff estate should also come in the description. A short write-up can be done to explain to the reader or supervisor the available facilities installed and used in the CBN staff quarters, for example, “ The facilities provided in the CBN staff quarters are; water treatment plant, cameras, sewage treatment plant, generator house, heavy duty generator set to illuminate the premises, pumping machine (Sumo) to circulate water to all apartments, borehole, external lighting points and lawn tennis court for exercise .”

Sometimes an institution could be a case study of a project. Let’s use this project topic as an example “ An Analysis of the Maintenance and Management Problem of the University of Lagos Hostel Buildings ”.

To describe this study area the following sub-headings should be developed and expanded:

This involves the description of the University’s location, including the city and local government area where it is situated.

The History, Origin and Growth of the Study Area:

Tracing the historical background of the University of Lagos, its various campuses, colleges (college of medicine), the total size of the school premises, total number of staff and students (undergraduates and postgraduate students), annual enrollment of students, the various faculties and departments and other facilities attached to the universities and subsidiary campuses or learning institutions within and outside the state, or country is paramount.

Important : Make sure to include a colour map in your description to guide your readers and supervisor further.

SAMPLE OF DESCRIPTION OF STUDY AREA

Frequently asked questions about the description of study area., what is the general description of the study area.

There is no such thing as a general description of the study area, the pattern of describing a particular area might differ from the way other areas are described. This is dependent on the type and nature of the area that is going to be described. No two locations have the same features, hence you cannot give a written account of locations A and B the same way, which is why the researcher will need to either visit the area of the study or source materials with comprehensive and recent information on a particular area to be described in the research paper.

Examples of areas of study?

The determination of a study area is dependent on the type or nature of the researchable problem that the researcher wants to solve. For example, an ideal study area for “Impact of indiscriminate dumps on children’s health” would be a neighbourhood that experiences a high volume of indiscriminate dumps such as ghettos, slum neighbourhoods, high-density or populated neighbourhoods etc.

Also, if a project topic is “Impact of social media on junior secondary school subjects” the area of study will comprise a certain number of junior secondary schools in a particular area not necessarily the entire State, Region or Province. The area of study must be connected with the project topic, this is because the research problem is first identified before developing a topic around the problem. So, the research has to identify a problem, search for areas affected by the identified problem and then develop a topic that captures the problem and the area of study.

The following can represent an area of study; Primary and Secondary Schools, Communities, Organizations, Provinces, Streets, Local Government Areas, hospitals, Banks, TV and Radio Stations, Government Agencies, Military Barracks, Police Stations, Specialized Buildings, Events, Shrines, Layouts etc.

Some people may want to carry out simple research about their home or certain areas or components in their home, this could be academic or personal research about an identified problem in the home. Hence, examples of study areas at home would include, the premises, building structures, the environment, farmland or plantation farm, auxiliary facilities, recreational areas in the home, pool sites, cooking or baking area etc. depending on the project topic.

What is a study area in research?

Study areas are locations where a researcher plans to carry out an in-depth study about a topic or existing problem. This is usually indicated in the research proposal for the supervisor to vet and approve. If approved, the researcher or student is expected to visit the study area to observe and gather information related to the existing problem in that neighbourhood. A study area is also referred to as a study site or research site.

What is the importance of the study area in research?

The importance of the study area cannot be over-emphasized. I have taken time to explain this question in the article “ Reasons for Choosing a Study Area in Research ”.

Must a description of the study area in a project be broad?

No. I mentioned earlier in this article that most research papers or projects require a brief description of your study area, so you could write a brief account of your study area in about one to three pages depending on how vast the area is. You don’t need to write more than is required, just provide the relevant information needed and you’re good.

Get complete samples of the Description of Study Areas here

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18 Replies to “HOW TO WRITE DESCRIPTION OF STUDY AREA IN RESEARCH” .

South Africa has been experiencing load-shedding

its educative

I am interested in your website. Currently I am preparing my thesis for completion of my MBA n Marketing. Thank you for your help.

Thank you Zelalem, you can send a message if you need further guide. I wish you success!

What if I choose a Senior high school in Enugu state? Am I going to write about the school or the State itself?

If your project topic is about a particular high school then the description should focus on the School itself not the State.

very good concept. Really I appreciate it.

Awesome, thanks Ray.

Helpful information .Thanks

Thank you Peres Bett.

How to write description of the study Area

This is great information just as I wanted it to be. thanks a lot man

Thanks Richard.

What important information should I include in the research area description? Regard Telkom University

What’s your study area?

My study area is Mbabane in Eswatini. However, am doing my thesis in an Asian University. Should my focus be with the Town or the entire Eswatini?

You may not be able to cover the entire Eswatini. So, delimit your study area to Mbabane. By the way, what’s your Thesis topic?

Study designs: Part 1 – An overview and classification

Priya ranganathan.

Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India

Rakesh Aggarwal

1 Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

There are several types of research study designs, each with its inherent strengths and flaws. The study design used to answer a particular research question depends on the nature of the question and the availability of resources. In this article, which is the first part of a series on “study designs,” we provide an overview of research study designs and their classification. The subsequent articles will focus on individual designs.

INTRODUCTION

Research study design is a framework, or the set of methods and procedures used to collect and analyze data on variables specified in a particular research problem.

Research study designs are of many types, each with its advantages and limitations. The type of study design used to answer a particular research question is determined by the nature of question, the goal of research, and the availability of resources. Since the design of a study can affect the validity of its results, it is important to understand the different types of study designs and their strengths and limitations.

There are some terms that are used frequently while classifying study designs which are described in the following sections.

A variable represents a measurable attribute that varies across study units, for example, individual participants in a study, or at times even when measured in an individual person over time. Some examples of variables include age, sex, weight, height, health status, alive/dead, diseased/healthy, annual income, smoking yes/no, and treated/untreated.

Exposure (or intervention) and outcome variables

A large proportion of research studies assess the relationship between two variables. Here, the question is whether one variable is associated with or responsible for change in the value of the other variable. Exposure (or intervention) refers to the risk factor whose effect is being studied. It is also referred to as the independent or the predictor variable. The outcome (or predicted or dependent) variable develops as a consequence of the exposure (or intervention). Typically, the term “exposure” is used when the “causative” variable is naturally determined (as in observational studies – examples include age, sex, smoking, and educational status), and the term “intervention” is preferred where the researcher assigns some or all participants to receive a particular treatment for the purpose of the study (experimental studies – e.g., administration of a drug). If a drug had been started in some individuals but not in the others, before the study started, this counts as exposure, and not as intervention – since the drug was not started specifically for the study.

Observational versus interventional (or experimental) studies

Observational studies are those where the researcher is documenting a naturally occurring relationship between the exposure and the outcome that he/she is studying. The researcher does not do any active intervention in any individual, and the exposure has already been decided naturally or by some other factor. For example, looking at the incidence of lung cancer in smokers versus nonsmokers, or comparing the antenatal dietary habits of mothers with normal and low-birth babies. In these studies, the investigator did not play any role in determining the smoking or dietary habit in individuals.

For an exposure to determine the outcome, it must precede the latter. Any variable that occurs simultaneously with or following the outcome cannot be causative, and hence is not considered as an “exposure.”

Observational studies can be either descriptive (nonanalytical) or analytical (inferential) – this is discussed later in this article.

Interventional studies are experiments where the researcher actively performs an intervention in some or all members of a group of participants. This intervention could take many forms – for example, administration of a drug or vaccine, performance of a diagnostic or therapeutic procedure, and introduction of an educational tool. For example, a study could randomly assign persons to receive aspirin or placebo for a specific duration and assess the effect on the risk of developing cerebrovascular events.

Descriptive versus analytical studies

Descriptive (or nonanalytical) studies, as the name suggests, merely try to describe the data on one or more characteristics of a group of individuals. These do not try to answer questions or establish relationships between variables. Examples of descriptive studies include case reports, case series, and cross-sectional surveys (please note that cross-sectional surveys may be analytical studies as well – this will be discussed in the next article in this series). Examples of descriptive studies include a survey of dietary habits among pregnant women or a case series of patients with an unusual reaction to a drug.

Analytical studies attempt to test a hypothesis and establish causal relationships between variables. In these studies, the researcher assesses the effect of an exposure (or intervention) on an outcome. As described earlier, analytical studies can be observational (if the exposure is naturally determined) or interventional (if the researcher actively administers the intervention).

Directionality of study designs

Based on the direction of inquiry, study designs may be classified as forward-direction or backward-direction. In forward-direction studies, the researcher starts with determining the exposure to a risk factor and then assesses whether the outcome occurs at a future time point. This design is known as a cohort study. For example, a researcher can follow a group of smokers and a group of nonsmokers to determine the incidence of lung cancer in each. In backward-direction studies, the researcher begins by determining whether the outcome is present (cases vs. noncases [also called controls]) and then traces the presence of prior exposure to a risk factor. These are known as case–control studies. For example, a researcher identifies a group of normal-weight babies and a group of low-birth weight babies and then asks the mothers about their dietary habits during the index pregnancy.

Prospective versus retrospective study designs

The terms “prospective” and “retrospective” refer to the timing of the research in relation to the development of the outcome. In retrospective studies, the outcome of interest has already occurred (or not occurred – e.g., in controls) in each individual by the time s/he is enrolled, and the data are collected either from records or by asking participants to recall exposures. There is no follow-up of participants. By contrast, in prospective studies, the outcome (and sometimes even the exposure or intervention) has not occurred when the study starts and participants are followed up over a period of time to determine the occurrence of outcomes. Typically, most cohort studies are prospective studies (though there may be retrospective cohorts), whereas case–control studies are retrospective studies. An interventional study has to be, by definition, a prospective study since the investigator determines the exposure for each study participant and then follows them to observe outcomes.

The terms “prospective” versus “retrospective” studies can be confusing. Let us think of an investigator who starts a case–control study. To him/her, the process of enrolling cases and controls over a period of several months appears prospective. Hence, the use of these terms is best avoided. Or, at the very least, one must be clear that the terms relate to work flow for each individual study participant, and not to the study as a whole.

Classification of study designs

Figure 1 depicts a simple classification of research study designs. The Centre for Evidence-based Medicine has put forward a useful three-point algorithm which can help determine the design of a research study from its methods section:[ 1 ]

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Classification of research study designs

Does the study describe the characteristics of a sample or does it attempt to analyze (or draw inferences about) the relationship between two variables? – If no, then it is a descriptive study, and if yes, it is an analytical (inferential) study
If analytical, did the investigator determine the exposure? – If no, it is an observational study, and if yes, it is an experimental study
If observational, when was the outcome determined? – at the start of the study (case–control study), at the end of a period of follow-up (cohort study), or simultaneously (cross sectional).

In the next few pieces in the series, we will discuss various study designs in greater detail.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

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3. Methodology of Research 3.1. Study Area and Target Population

Related Papers

Cherinet Bariso

International Scholars Journals

MASARAT E L I A S DURESSO (PhD)

Among the major root and tuber crops, anchote is a potential crop produced in Western parts of Ethiopia. In addition to food source, it takes wide portion in socioeconomic , cultural and medicinal value for the farming communities. To study the indigenous knowledge on utilization and conservation of anchote, ethno-botanical survey was conducted in 2012 for continuous three months (February, March and April) in Western part of Ethiopia. The landraces were also collected during survey. Forty nine anchote landraces were tested in 7x7 Simple Lattice Design at Wayu Tuqa District of East Wollega in 2012/013. The survey results showed that most of the respondents had sufficient experiences of growing Coccinia abyssinica (Lam.) Cogn. Socioeconomic status of the households and ecological requirements was found to be an important factor affecting the use, management and conservation of the crop. The difference in level of education had no impact on conservation and use of Coccinia abyssinica. It was also observed that the older informants were more knowledgeable than the younger ones, as they knew much more about the different local cultivars and values of use. Data of the mean values of all experimental units were subjected to analysis of variance for RCBD. Flower width (61.22%) showed high heritability and medium heritability was recorded for flower length (52.24%), indicated that such characters were least affected by environmental modifications so that; selection based on phenotypic performance would be reliable. Low heritability were recorded for traits like root length (33.72%), Leaf width (21.53%), total root yield (20.6%), leaf length (17.19%), root diameter (8.33%) and low heritability were recorded for other to indicate environmental effect that constitutes a major portion of the total phenotypic variation signifying that management practice is better than selection to improve those traits. Genetic advance as percentage of the mean ranged from 2.45% for leaf length to 77.08% for flower width. Within these range a relatively high genetic advance as percent of the mean was observed for flower length (57.72%) and flower width (77.08 %). High value for heritability and genetic advance of the characters in current study provide information for the existence of wider genetic diversity among anchote landraces which offers high chances for improving several traits of the crop through simple selection. Cluster analysis showed that four divergent groups were formed. Each cluster known by their highest and lowest mean value and it is helpful for easy selection of parents with the desired traits for hybridization or selection program.

Urgessa T Bekabil

Deforestation is a growing problem in many parts of the tropical world and one of the affected countries is Ethiopia. The general objective of this study is to assess the effect of population growth on forest resource in East Wollega Zone in general and Haro Limu woreda in particular. The data used for the study were collected from 89 farm households heads drawn from the four kebeles of Haro Limmu district. Probability proportional to size sampling technique was employed to select the farm households from four peasant associations, which were selected by random sampling techniques. Primary data were collected using a structured questionnaire. In addition, secondary data were extracted from relevant sources to supplement the data obtained from the survey. The result of this study reveals that population growth huge impact on forestry development in the ways of expanding agricultural land, using wood as energy sources and satisfying the input requirements in agricultural activity. Respondents use family planning services in reducing the impact of population growth on the forestry development.

addisu N Worku

Mersha Chanie

This study was conducted in Honkolo enclosed area found in Honkolo Wabe district of Arsi zone with in oromia region. The study objective was to critically assess the land use land cover change in Honkolo enclosed area, and explain socioeconomic and environmental impacts caused due to land use land cover change. To realize the objective data was collected from 95 sample rural households using questionnaire, 6 key informant interviews, and 4 Focus Group discussions with farmers and experts. Besides to this, satellite image of 30 meter resolution was also used to identify the land use and land cover change in the enclosed area with remote sensing and GIS software. The analysis of land use land cover change detection showed that farm land and settlement had been increasing from before the area was enclosed from human and animal interventions since 2010; the socioeconomic analysis revealed woody tree species that disappeared long time ago have been restored following the establishment of enclosures. Additionally, most of focus group discussion and key informant confirmed that they had obtained socio-economic and environmental benefits from the establishment of the area enclosures. From the analysis of the results on LULC it can be concluded that human interventions are the determinant factors for the changing land use and land cover. However, various problems were also identified such as shortages of firewood and scarcity of pastureland. Finally based on findings it is concluded that local community had got a positive attitude towards area enclosures practices. Therefore, close relationship among the local communities and other related bodies is essential for the success and effective management practices of area enclosures. Key words: Area enclosure, Land use/land over, land management, Land degradation, GIS, community participation

European Scientific Journal ESJ

Jiregna Garamu Tarafa

Abstract The main objective of this study was to examine, the population growth nexus land degradation in Nejo district. Correlation research design was used to carry out this study. Both quantitative and qualitative data used in the study. Primary and secondary data were used in this study. Non-probable sampling techniques were used to select the four peasant association from thirty-five of Nejo district, namely Walitate Agar, Bushane Alaltu, Micico Gorgise, and Lalisa Kemi. This was due to insufficient budget and time to include overall peasant associations in the district. Sampling formula used to determine sample of 99 households and were selected from the total of 3559 households using lottery method proportionally. Additional key informant like, DA (Development Agents) and district agricultural office head were interviewed and, model farmers participated in focus group discussion. Questionnaire presented to collect data from households, semi-structured interview used to complement data gathered using questionnaires from DA and district agricultural office.Focus group discussion also instruments used for data collection from model farmers. Finally, researcher undertakes field observation the land use and extent of physical land degradation. Quantitative data were analyzed using excel software package to compute its frequencies, percentage, means and standard deviation, Pearson correlation and linear regressions followed by discussion of the most important points. Data that were collected by semi-structure interview and open- ended questions were analyzed and interpreted in narrative approach to substantiate the quantitative information whenever required. Finally, the overall courses of the study was summarized with finding, conclusions some possible solution. The finding showed that as population growth non-cultivated areas added as crop land and the more use of other land uses for crop production. There is a significant negative correlation between areas land covered with grazing lands and population growth in the district.There is a significant negative correlation between areas of natural forest and population growth. Population growths have significant negative relationship with grazing lands. The population growths have significant positive relationship with grazing lands.The findings revealed that the population growth have no significant relationship with changes in areas of wet lands as.With respect to linear regressions were utilized to investigate the best indicators of changes in areas of forest plantation. The findings revealed that the population growth have significant positively relationship with forest plantation with hence population growth constitute the major determinants of land degradation as there were effect changing in land use cover of in Nejo district.The respondents were asked if they think that land degradation affects your livelihood. All of the respondents had agreed that land degradation affects their livelihood. The major costs of land degradation includes, reduced number of daily meals, reduced in quality of meals, withdrawal of children from school, poor health, lack of household energy consumptions such as fire wood & charcoal, decline in livestock caring capacity, decrease in range land, poverty and malnutrition, andinternalmigration. Based on finding the study drawn following recommendation the farmers need participate effectively throughout the entire district to assist in reducing the pressure on available land and vegetation resources in the district. The need to use alternative sources of energy like solar in medium and long-term and promote the growing of fast maturing tree species for sustainable charcoal production.

Temesgen Sadi

This study attempts to assess the challenges and prospects of community policing in Nejo town, Oromia regional state. In order to achieve this objective, the study employed descriptive research design and combination of quantitative and qualitative research approach. The study used both primary and secondary sources in order to touch its objectives. Primary data were gathered through questionnaire, interview and focus group discussion while secondary data were gathered through document analysis, books, journal and other document. Questionnaires were distributed and administered by the researcher with the help of enumerators. Structured questionnaires were filled by households of 01 and 04 kebeles. Interviews were conducted with police members, community leaders and justice sector participants to attain profound information. Similarly, FGD was conducted with respondents selected from police and community members. Data were analyzed and interpreted using descriptive statistics and qualitative technique.The finding of the study revealed that, community and to some extent police have low understanding and perception toward community policing in the study area. In addition to this, the study identified institutional challenges, which include lack of coordination, lack of effective police service delivery, lack of professional police and police violation of human right. Similarly, the study identified social challenges affecting community policing, which include, lack of community participation, lack of police community relationship and lack of regular community policing forum. Under infrastructural challenges the study identified lack of adequate logistic support, lack of adequate budge and lack of resource to implement community policing effectively. The finding of the study also revealed that the practice of the key components of community policing mainly community partnership, problem solving and organizational transformations are not as such effective. Based on the finding of the study, the researcher recommends that enhancing awareness creation, effective coordination among the stakeholders, insuring transparency and accountability, building trust with community, establishing regular community policing forum, enhancing police capacity, allocating adequate budget and logistic support, improving community participation in order to sustain these strategies in the study area.

IJAR Indexing

This study attempted to arrive at the ways of indigenous practices for promoting sustainable land development in selected kebeles of Gimbi Woreda,West Wollega Zone, Oromia Regional State. The study area is typical for the high potential coffee production, mixed farming, and cereal crops in the Southwestern Ethiopian highlands. Land is a precious natural resource which demands efficient management in order to use it in a sustainable manner. A cross sectional research design was employed with descriptive survey method. About 319 household heads were selected using simple random sampling technique from three kebeles (kebele: Lowest Administrative Division) which were chosen purposively. In addition, thirteen key informants and nine household heads for FGD were selected by purposive sampling technique. Data collection tools included questionnaire, focus group discussions, key informant interview and field observation. The factors that affect sustainable land management include land holding size, fragmentation, land ownership security, size of livestock, and availability of labor and farm tools, and education of farmers. Finally, based on the findings of the study, it has been recommended that farmers need to get basic education and family planning services. They have to be organized in team and get access to credit and saving services. The local knowledge of farmers has to be encouraged and supported through continuous training. A few selected breeds of livestock should be encouraged in order to reduce overgrazing.

3. The Study Area: Definition and Characteristics

From the book managed integration.

Harvey Luskin Molotch
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Supplementary Materials

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Selecting Research Area

Selecting a research area is the very first step in writing your dissertation. It is important for you to choose a research area that is interesting to you professionally, as well as, personally. Experienced researchers note that “a topic in which you are only vaguely interested at the start is likely to become a topic in which you have no interest and with which you will fail to produce your best work” [1] . Ideally, your research area should relate to your future career path and have a potential to contribute to the achievement of your career objectives.

The importance of selecting a relevant research area that is appropriate for dissertation is often underestimated by many students. This decision cannot be made in haste. Ideally, you should start considering different options at the beginning of the term. However, even when there are only few weeks left before the deadline and you have not chosen a particular topic yet, there is no need to panic.

There are few areas in business studies that can offer interesting topics due to their relevance to business and dynamic nature. The following is the list of research areas and topics that can prove to be insightful in terms of assisting you to choose your own dissertation topic.

Globalization can be a relevant topic for many business and economics dissertations. Forces of globalization are nowadays greater than ever before and dissertations can address the implications of these forces on various aspects of business.

Following are few examples of research areas in globalization:

A study of implications of COVID-19 pandemic on economic globalization
Impacts of globalization on marketing strategies of beverage manufacturing companies: a case study of The Coca-Cola Company
Effects of labour migration within EU on the formation of multicultural teams in UK organizations
A study into advantages and disadvantages of various entry strategies to Chinese market
A critical analysis of the effects of globalization on US-based businesses

Corporate Social Responsibility (CSR) is also one of the most popular topics at present and it is likely to remain so for the foreseeable future. CSR refers to additional responsibilities of business organizations towards society apart from profit maximization. There is a high level of controversy involved in CSR. This is because businesses can be socially responsible only at the expense of their primary objective of profit maximization.

Perspective researches in the area of CSR may include the following:

The impacts of CSR programs and initiatives on brand image: a case study of McDonald’s India
A critical analysis of argument of mandatory CSR for private sector organizations in Australia
A study into contradictions between CSR programs and initiatives and business practices: a case study of Philip Morris Philippines
A critical analysis into the role of CSR as an effective marketing tool
A study into the role of workplace ethics for improving brand image

Social Media and viral marketing relate to increasing numbers of various social networking sites such as Facebook, Twitter, Instagram, YouTube etc. Increasing levels of popularity of social media among various age groups create tremendous potential for businesses in terms of attracting new customers.

The following can be listed as potential studies in the area of social media:

A critical analysis of the use of social media as a marketing strategy: a case study of Burger King Malaysia
An assessment of the role of Instagram as an effective platform for viral marketing campaigns
A study into the sustainability of TikTok as a marketing tool in the future
An investigation into the new ways of customer relationship management in mobile marketing environment: a case study of catering industry in South Africa
A study into integration of Twitter social networking website within integrated marketing communication strategy: a case study of Microsoft Corporation

Culture and cultural differences in organizations offer many research opportunities as well. Increasing importance of culture is directly related to intensifying forces of globalization in a way that globalization forces are fuelling the formation of cross-cultural teams in organizations.

Perspective researches in the area of culture and cultural differences in organizations may include the following:

The impact of cross-cultural differences on organizational communication: a case study of BP plc
A study into skills and competencies needed to manage multicultural teams in Singapore
The role of cross-cultural differences on perception of marketing communication messages in the global marketplace: a case study of Apple Inc.
Effects of organizational culture on achieving its aims and objectives: a case study of Virgin Atlantic
A critical analysis into the emergence of global culture and its implications in local automobile manufacturers in Germany

Leadership and leadership in organizations has been a popular topic among researchers for many decades by now. However, the importance of this topic may be greater now than ever before. This is because rapid technological developments, forces of globalization and a set of other factors have caused markets to become highly competitive. Accordingly, leadership is important in order to enhance competitive advantages of organizations in many ways.

The following studies can be conducted in the area of leadership:

Born or bred: revisiting The Great Man theory of leadership in the 21 st century
A study of effectiveness of servant leadership style in public sector organizations in Hong Kong
Creativity as the main trait for modern leaders: a critical analysis
A study into the importance of role models in contributing to long-term growth of private sector organizations: a case study of Tata Group, India
A critical analysis of leadership skills and competencies for E-Commerce organizations

COVID-19 pandemic and its macro and micro-economic implications can also make for a good dissertation topic. Pandemic-related crisis has been like nothing the world has seen before and it is changing international business immensely and perhaps, irreversibly as well.

The following are few examples for pandemic crisis-related topics:

A study into potential implications of COVID-19 pandemic into foreign direct investment in China
A critical assessment of effects of COVID-19 pandemic into sharing economy: a case study of AirBnb.
The role of COVID-19 pandemic in causing shifts in working patterns: a critical analysis

Moreover, dissertations can be written in a wide range of additional areas such as customer services, supply-chain management, consumer behaviour, human resources management, catering and hospitality, strategic management etc. depending on your professional and personal interests.

[1] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited.

John Dudovskiy

How to write the perfect study description

The secret to getting quality data for your research study is recruiting quality participants – who are eager, enthusiastic, and engaged. But just how do you do that?

Your study description can help. It's an often-overlooked aspect of study design that can greatly influence who you bring on board, and the results they give you.

Why your study description matters

Your title and description are the first things potential participants see when they’re scrolling through, looking for their next study.

If they’re compelling, they won’t just catch a participant’s eye. They’ll also provide all the information they need to decide whether they’ll participate in your study.

What’s the aim of the study? What does the participant need to do? Will they have to give any sensitive information? Is there anything in the study that might make them uncomfortable? These are the kinds of things a participant will want to know before getting involved.

Written well, a study description makes your instructions clearer. And it can make your participants feel more motivated. After all, participants are more likely to immerse themselves in your study if they understand its purpose and what’s expected of them.

What’s more, a good study description can help you meet certain ethical requirements, such as gaining informed consent from participants.

The key here is to include just the right amount of information the participant will need to decide whether to partake.

Too much, and you risk not only giving away the aims of your study, but also boring the reader – driving them to scroll on. Too little, and they won’t know what they’re possibly getting themselves into, or fully understand what’s expected of them.

Here are the elements we recommend you include:

The aim of the study

Include a clear and concise statement about what the study is trying to achieve – without divulging too much, so as not to influence responses.

Participant requirements

Clearly outline what the participant will need to do. This includes any instructions, materials, or equipment they’ll require.

Sensitive information

If you need any sensitive data from a participant, let them know. This includes personal or medical details.

Uncomfortable tasks

Warn participants about any sections they may find uncomfortable. This could be viewing disturbing images or videos, for instance.

Unusual requests

Warn participants of anything unexpected they will need to do, such as downloading software or requiring headphones.

Rejection prevention

Instruct participants on what they must do to avoid their submission being rejected, such as completing all tasks or answering all questions.

Reward details

Give participants an estimate of how long it’ll take to receive a reward after submission. If you plan to use bonus payments, or if it’s a longitudinal study with a payment schedule, then state this clearly.

Opt-out instructions

Discuss how a participant can opt out of the study, and what will happen if they do.

Data removal information

Let participants know whether they can remove their data from the dataset, and provide instructions on how to do so.

Data accessibility information

Explain whether anonymized data will be made accessible to other researchers, and how the data will be used (e.g., to publish a research study or guide government policy).

Contact details

Provide your contact details in case participants have questions. If you have ethics approval, include the contact details of the ethics board in question.

Don’t forget to debrief

At the end of your study, it's important to provide participants with a debriefing. This serves three purposes: it provides closure for the participant, it makes sure they leave the study with a positive impression, and it allows you to address any issues that arose during the study.

If you used deception or a cover story during the study, make sure to resolve this in the debriefing. The debriefing should consist of a short thank you message, as well as information about any deception that was used in the study.

In some cases, you might also want to give contact details for relevant helplines. An addiction support helpline would be pertinent after a study on drug abuse, for example.

In conclusion

A well-written study description is a win-win for you and the people taking part. It ensures participants know exactly what they need to do and have the motivation to do it. And it helps you gather valuable, quality data.

By providing participants with clear instructions and information about the study's purpose, you’ll set them up to give the best responses they can, and minimize the risk of incomplete or inaccurate data.

To learn more tips and tricks for running effective research and receiving high-quality data, download our best practice guide today.

High-quality human data to deliver world-leading research and AIs.

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Analysis of Rankings of Causal Factors of Substance Use

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Elizabeth Mathews , Liberty University Follow

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This study investigates and compares causal factors associated with substance use among both students and professionals. This study focuses on a range of biological, environmental, and psychological evidence-based causal factors for substance use and misuse. The goal of this research is to explore how novices and experts conceptualize factors related to substance use. Forty-seven residential undergraduate psychology students from Liberty University participated in evaluating 18 evidence-based causal factors using concept mapping to explain how implicit cognitive processing – rather than just explicit processing – informs substance use risk. Additionally, professionals in psychology, counseling, and social work in the general Lynchburg area will create concept maps using these same causal factors based on their experiences working with clients with substance use disorder. The visual representation collected from each concept map will be used to generate a ranked list of these factors, which will be compared across subjects. We expect that professionals' rankings of these causal factors will align more closely with the literature and that their concept maps will be more complex than students. The findings aim to inform the development of education, clinical, and prevention efforts by better understanding differing understandings of substance use based on individuals' histories or exposure to substance use or formal education.

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The blue histogram bars depict the frequency of T scores among participants per Child Behavior Checklist index scale including the internalizing problems scale (A), externalizing problems scale (B), and total problems scale (C). Frequencies and percentages are based on a total of 229 participants.

eFigure 1. Participant Selection Flowchart for the Current Study Sample

eFigure 2. Directed Acyclic Graph (DAG) for Covariate Selection

eTable 1. Maternal Demographics According to Fluoride Sample

eFigure 3. Distributions of Raw Scores for CBCL Syndrome Scales Among Children in the MADRES Study at Age 3; n = 229

eFigure 4. Distributions of Raw Scores for CBCL DSM-Oriented Scales Among Children in the MADRES Study at Age 3; n = 229

eTable 2. CBCL Scores at Age 36-Months in the MADRES Cohort

eTable 3. Poisson Regression Estimating the Risk Ratio for Third Trimester MUFsg in Relation to CBCL Clinical Index Scores

eTable 4. Sensitivity Analysis Including “Borderline Clinical” with “Non-Clinical” Group as the Reference in Logistic Regression of Trimester 3 MUFsg With CBCL Clinical Index Scores

eTable 5. Sensitivity Analysis of Associations of MUFsg in Trimester 1 With CBCL Clinical Index Scores

eTable 6. Sensitivity Analysis of Associations of Trimester 1 MUFsg With Composite T-Scores, and Syndrome or DSM Scale Raw CBCL Scores at Age 3

eTable 7. Associations of MUFsg in Trimester 1 with CBCL Scores Adjusting for Blood Lead

eTable 8. Associations of MUFsg in Trimester 3 With CBCL Scores Adjusting for Trimester 1 Blood Lead

eTable 9. Associations of MUFsg in Trimester 3 with CBCL Clinical Index Scores Adjusting for Trimester 1 Blood Lead

eTable 10. Associations of MUFsg in Trimester 3 with CBCL Scores Among Women Who Fasted for ≥ 8 Hours

eTable 11. Trimester 3 MUFsg in Relation to CBCL Clinical Index Scores Among Women who Fasted for ≥ 8 Hours

eTable 12. Associations of MUFsg in Trimester 3 with CBCL Scores Including Women Who Smoked During Pregnancy

eTable 13. Trimester 3 MUFsg in Relation to CBCL Clinical Index Scores Including Women Who Smoked During Pregnancy

eTable 14. Associations of Average MUFsg Across Trimesters 1 and 3 With CBCL Scores

eTable 15. Average MUFsg Across Trimesters 1 and 3 in Relation to CBCL Clinical Index Scores

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Malin AJ , Eckel SP , Hu H, et al. Maternal Urinary Fluoride and Child Neurobehavior at Age 36 Months. JAMA Netw Open. 2024;7(5):e2411987. doi:10.1001/jamanetworkopen.2024.11987

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Maternal Urinary Fluoride and Child Neurobehavior at Age 36 Months

1 Department of Epidemiology, College of Public Health and Health Professions University of Florida, Gainesville
2 College of Medicine, University of Florida, Gainesville
3 Department of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles
4 Department of Dental Public Health and Dental Informatics, School of Dentistry, Indiana University, Indianapolis

Question Is prenatal fluoride exposure associated with child neurobehavior in a US-based sample?

Findings In this cohort study of 229 pregnant women and their children, a 0.68 mg/L (ie, 1 IQR) increase in specific gravity–adjusted maternal urinary fluoride during pregnancy was associated with nearly double the odds of T scores for total child neurobehavioral problems being in the borderline clinical or clinical range.

Meaning These findings suggest that prenatal fluoride exposure may increase risk of neurobehavioral problems among children living in an optimally fluoridated area in the US.

Importance Recent studies in Canadian and Mexican populations suggest an association of higher prenatal fluoride exposure with poorer neurobehavioral development, but whether this association holds for US-based populations is unknown.

Objective To examine associations of third trimester maternal urinary fluoride (MUF) with child neurobehavior at age 3 years in the US.

Design, Setting, and Participants This prospective cohort study utilized urine samples archived from 2017 to 2020 and neurobehavioral data assessed from 2020 to 2023 from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) pregnancy cohort, which consisted of predominately Hispanic women residing in Los Angeles, California. Cohort eligibility criteria at recruitment included being 18 years of age or older, less than 30 weeks’ gestation, and a fluent English or Spanish speaker. Exclusion criteria included having a disability preventing participation or provision of informed consent, being HIV positive or incarcerated, and having a multiple gestation pregnancy. There were 263 mother-child pairs who completed the 3-year study visit. In this analysis, women who reported prenatal smoking were excluded. Data analysis was conducted from October 2022 to March 2024.

Exposure Specific gravity-adjusted MUF (MUF SG ), a biomarker of prenatal fluoride exposure.

Main Outcomes and Measures Neurobehavior was quantified using the Preschool Child Behavior Checklist (CBCL), which included composite scores for Total Problems, Internalizing Problems, and Externalizing Problems. CBCL composite T scores range from 28 to 100. T scores from 60 to 63 are in the borderline clinical range, whereas scores above 63 are in the clinical range. Linear and logistic regression models adjusted for covariates were conducted.

Results A total of 229 mother-child pairs (mean [SD] maternal age, 29.45 [5.67] years; 116 female children [50.7%] and 113 male children [49.3%]) who had MUF SG measured were included in the study. Median (IQR) MUF SG was 0.76 (0.51-1.19) mg/L, and 32 participants (14.0%) had a Total Problems T score in the borderline clinical or clinical range. A 1-IQR (0.68 mg/L) increase in MUF SG was associated with nearly double the odds of the Total Problems T score being in the borderline clinical or clinical range (odds ratio, 1.83; 95% CI, 1.17-2.86; P = .008), as well as with a 2.29-point increase in T score for the Internalizing Problems composite (B = 2.29; 95% CI, 0.47-4.11; P = .01) and a 2.14-point increase in T score for the Total Problems composite (B = 2.14; 95% CI, 0.29-3.98; P = .02).

Conclusions and Relevance In this prospective cohort study of mother-child pairs in Los Angeles, California, prenatal fluoride exposure was associated with increased neurobehavioral problems. These findings suggest that there may be a need to establish recommendations for limiting fluoride exposure during the prenatal period.

Fluoride levels in community drinking water systems in the US have been adjusted to prevent dental caries since 1945. 1 Currently, 73% of the US receives fluoridated water at a targeted concentration of 0.7 mg/L (to convert to millimoles per liter, multiply by 0.05263). This has been considered optimal for preventing dental caries while minimizing risk of adverse systemic health effects. 2 Most of Los Angeles County, California is at least partially fluoridated. 3 , 4 Fluoride can also naturally occur in soil and rock or be released into the environment via industrial processes. 5 , 6

It is widely established that exposure to high fluoride levels can adversely affect neurodevelopment 7 ; however, findings from recent studies conducted in Mexico and Canada 8 - 11 suggest that fluoride exposure at lower US-relevant levels may also be associated with poorer neurodevelopment. Specifically, higher prenatal fluoride exposure in Canada and/or Mexico has been associated with lower IQ among children aged 3 to 4 years in Canada 10 and children aged 6 to 12 years in Mexico, 9 increased symptoms of attention-deficit/hyperactivity disorder (ADHD) among children aged 6 to 12 years, 12 poorer executive function among children aged 3 to 5 years, 13 and poorer performance on measures of global cognition among 12- and 24-month-old boys. 14 A recent systematic review conducted by the National Toxicology Program reported “with moderate confidence that higher fluoride exposure…is consistently associated with lower IQ in children.” 15 The report 15 also highlighted the lack of US studies investigating associations of fluoride exposure with neurodevelopment or cognition and stated that US studies would be valuable. To our knowledge, we conducted the first, US-based study to examine associations of prenatal fluoride exposure with child neurobehavioral outcomes.

This cohort study was approved by the institutional review boards at The University of Southern California and The University of Florida and followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. This study included mother-child pairs from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) cohort. 16 MADRES is a prospective pregnancy cohort consisting of 1065 predominately Hispanic women of low socioeconomic status residing in urban Los Angeles, California. 16 Briefly, in 2015, pregnant women were recruited from prenatal care clinicians in Los Angeles serving predominantly medically underserved communities and provided written informed consent. Eligibility criteria include being 18 years of age or older, less than 30 weeks’ gestation at the time of recruitment, and being able to speak English or Spanish fluently. Exclusion criteria included having a multiple gestation pregnancy; being HIV positive; having a physical, mental, or cognitive disability that would prevent participation or provision of informed consent; and current incarceration. 16 The current study included mother-child pairs from the MADRES prospective cohort who had maternal urinary fluoride (MUF) measured during the third trimester of pregnancy and child scores on the Preschool Child Behavior Checklist (CBCL) for ages 1.5 to 5 years at age 36 months (eFigure 1 in Supplement 1 ).

Single spot urine samples were collected from MADRES participants during the third trimester of pregnancy (from 2017-2020). The mean (range) gestational age at third trimester urine collection was 31.6 (26.9-36.0) weeks. MUF was measured at the Oral Health Research Institute at the Indiana University School of Dentistry using the Martinez Mier et al modification 17 , 18 of the hexamethyldisiloxane microdiffusion method of Taves et al 19 (see the eMethods in Supplement 1 for additional details). MUF measurements were adjusted for specific gravity (MUF SG ). Urinary fluoride was utilized because it provides a reliable measure of total fluoride intake. It is also the most widely employed measure of individual fluoride exposure in epidemiological studies, including those assessing neurodevelopment. 10 - 12 , 20 , 21

We examined child neurobehavioral problems. These included internalizing and externalizing symptoms and symptoms consistent with Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition [ DSM-5 ]) diagnostic categories.

Child neurobehavioral outcomes were assessed from 2020 to 2023 via the Preschool CBCL, a valid measure of neurobehavior. 22 - 24 The Preschool CBCL is a parent-reported measure of 99 items that was administered in MADRES when the child was approximately 36 months old. Children were rated on the CBCL by their mothers. The CBCL is available in English and Spanish. CBCL scores comprise 7 syndrome scales (Emotionally Reactive, Anxious-Depressed, Somatic Complaints, Withdrawn, Sleep Problems, Attention Problems, and Aggressive Behavior) characterizing problems that tend to co-occur together. The CBCL also includes 5 DSM-5 –oriented scales that are comprised of items determined to be consistent with DSM-5 diagnostic categories (Depressive Problems, Anxiety Problems, Oppositional Defiant Problems, Autism Spectrum Problems, and ADHD Problems). Scores on CBCL syndrome scales are grouped to produce an Internalizing Problems composite score and Externalizing Problems composite score. Scales that focus primarily on issues within the self comprise the Internalizing Problems composite. Conversely, scales that focus on other-directed problems and expectations for the child comprise the Externalizing Problems composite. Lastly, a Total Problems composite score is calculated by summing scores on all 99 items. 24 Internalizing Problems, Externalizing Problems, and Total Problems composite T scores range from 28 to 100. T scores ranging from 60 to 63 are in the borderline clinical range, whereas those above 63 are in the clinical range. 24 We calculated 2-category clinical index variables of normal vs borderline clinical or clinical for statistical analyses for each composite variable (see the eMethods in Supplement 1 for additional details about the CBCL scales).

Covariates were selected using a directed acyclic graph (eFigure 2 in Supplement 1 ), and included maternal age (continuous), education (less than 12th grade, completed 12th grade, some college or technical school, completed college, and some graduate training), ethnicity by nativity (non-Hispanic, US-born Hispanic, or non–US-born Hispanic), marital status (decline to answer, married, living together, never married and single, divorced or separated, or widowed), prepregnancy body mass index (continuous; calculated as weight in kilograms divided by height in meters squared) and prenatal household income (unknown,<$15 000, $15 000-$29 999, $30 000-$49 999, $50 000-$99 999, and ≥$100 000), as well as child sex. Categories for ethnicity by nativity were defined by study principal investigators, and ethnicity was included because it has been shown to be associated with fluoride exposure and neurodevelopment. We adjusted for ethnicity as a proxy for structural racism rather than as a biological difference. We recoded marital status based on cohabitation status (eMethods in Supplement 1 ).

Descriptive statistics were calculated for MUF SG , sociodemographic variables, and scores on the CBCL. We conducted linear regression adjusted for covariates to examine associations of third trimester MUF SG with CBCL composite T scores as well as raw scores on CBCL syndrome scales and DSM-5 –oriented scales. Assumptions of linear regression were satisfied for models examining associations of MUF SG with CBCL composite T scores; however, for several models examining associations of MUF SG with CBCL syndrome scales and DSM-5 –oriented scales, linear regression assumptions were not satisfied. Therefore, a natural logarithm transformation was applied and a constant of 1 was added (to account for scores of 0) to the raw scores for these scales to satisfy linear regression assumptions (see the eMethods in Supplement 1 for an expanded statistical analysis plan). We also tested whether child sex modified associations of MUF SG with CBCL scores by including a MUF SG × sex term in regression models to be retained if statistically significant. We conducted logistic regression examining associations of MUF SG with binary clinical index variables. Additionally, in sensitivity analyses, we conducted Poisson regression with robust error variances to determine the relative risk of scoring in the normal compared with borderline clinical or clinical range for clinical index variables. We also conducted binary logistic regression that included 2-category clinical index dependent variables of nonclinical (ie, normal or borderline) vs clinical for each clinical index variable. We conducted several additional sensitivity analyses that are reported in the eMethods in Supplement 1 . We excluded women who reported prenatal smoking (6 participants). Statistical analyses were performed using SPSS statistical software version 28 (IBM) and STATA/MP version 13.0 (Stata Corp). The criterion for statistical significance was an α < .05. Data analysis occurred from October 2022 to March 2024.

There were 229 mother-child pairs (mean [SD] maternal age, 29.45 [5.67] years; 116 female children [50.7%] and 113 male children [49.3%]) included in this study. See Table 1 for sociodemographic characteristics and exposure variables. For a comparison of sociodemographic characteristics between the current study sample and overall MADRES cohort with a live birth, see eTable 1 in Supplement 1 . Most participants (192 participants) reported fasting in the third trimester for at least 8 hours. MUF SG did not differ between women who reported fasting and those who did not. Median (IQR) MUF SG was 0.76 (0.51-1.19) mg/L. Mean (SD) T scores were 47.69 (11.60) for the Total Problems composite, 47.13 (11.62) for the Internalizing Problems composite, and 46.48 (10.68) for the Externalizing Problems composite ( Figure ). Of all participants, 32 (14.0%) had a Total Problems T score in the borderline clinical or clinical range, 35 (15.3%) had an Internalizing Problems T score in the borderline clinical or clinical range, and 23 (10.0%) had an Externalizing Problems T score in the borderline clinical or clinical range. Descriptive statistics for CBCL syndrome and DSM-oriented scale raw scores are presented in eFigure 3, eFigure 4, and eTable2 in Supplement 1 .

Associations of MUF SG with CBCL composite T scores and binary clinical index variables are presented in Table 2 . A 1-IQR (0.68 mg/L) increase in MUF SG was associated with nearly double the odds of having a Total Problems T score in the borderline clinical or clinical range compared with the normal range (odds ratio [OR], 1.83; 95% CI, 1.17-2.86; P = .008). Additionally, a 1-IQR increase in MUF SG was associated with a 2.29-point increase in Internalizing Problems T scores (B = 2.29; 95% CI, 0.47-4.11; P = .01) and 2.14-point increase in Total Problems T scores (B = 2.14; 95% CI, 0.29-3.98; P = .02). Associations of MUF SG with Externalizing Problems T scores or odds of having an Internalizing Problems T score in the borderline clinical or clinical range compared with the normal range were also positive but not statistically significant ( Table 2 ). Risk ratios were generally consistent with these ORs; however, magnitudes were smaller, and the P value for the risk ratio for the Internalizing Problems binary clinical index variable was statistically significant (eTable 3 in Supplement 1 ). Sensitivity analyses that included nonclinical vs clinical index dependent variables were also consistent (eTable 4 in Supplement 1 ).

Associations of MUF SG with raw scores for CBCL syndrome scales and DSM-5 –oriented scales are presented in Table 3 . A 1-IQR increase in MUF SG was associated with a 13.54% increase in raw scores for the Emotionally Reactive CBCL syndrome scale (B = 0.13; 95% CI, 0.02-0.24; P = .02), and a 19.60% increase in raw scores for the Somatic Complaints CBCL syndrome scale (B = 0.18; 95% CI, 0.07-0.28; P = .001). Additionally, a 1-IQR increase in MUF SG was associated with an 11.29% increase in scores on the DSM-5 –oriented Anxiety Problems scale of the CBCL (B = 0.11; 95% CI, 0.003-0.21; P = .045) and an 18.53% increase in scores on the DSM-5 –oriented Autism Spectrum Problems scale of the CBCL (B = 0.17; 95% CI, 0.04-0.30; P = .009). There were no other associations of MUF SG with other syndrome scales or DSM-5 –oriented scales. There was no interaction between fluoride and sex.

MUF SG during the first trimester was also positively associated with CBCL scores (eTable 5 and eTable 6 in Supplement 1 ) and when first trimester blood lead level was included as a covariate in sensitivity analyses, the magnitudes of associations became larger and previously nonsignificant findings became significant associations in models for both the first and third trimester (eTables 7-9 in Supplement 1 ). Associations of MUF SG with CBCL scores in the third trimester remained generally the same when examined among only the sample of women who fasted for at least 8 hours (192 participants) and when adjusting for maternal smoking during pregnancy (eTables 10-13 in Supplement 1 ). Lastly, magnitudes of associations of mean MUF SG across the first and third trimesters with CBCL scores were larger than associations of MUF SG in only the third trimester with CBCL scores (eTable 14 and eTable 15 in Supplement 1 ).

To our knowledge, this is the first US-based cohort study to examine associations of prenatal fluoride exposure with child neurobehavior. The study sample resided in a predominately fluoridated region and had fluoride exposures that are typical of those living in fluoridated communities in North America. 17 , 25 , 26 For example, Till et al 25 reported a median MUF SG of 0.77 mg/L among women living in fluoridated communities in Canada. We found that women with higher fluoride exposure during pregnancy tended to rate their children higher on overall neurobehavioral problems and internalizing symptoms, including emotional reactivity, anxiety, and somatic complaints by age 3 years. Furthermore, each 0.68 mg/L increase in MUF SG was associated with nearly double the odds of total neurobehavioral problems being in the borderline clinical or clinical range. Women with higher MUF SG during pregnancy also tended to rate their children higher on Autism Spectrum Disorder symptoms. The effect sizes observed in this study are sizable considering the relatively low urinary fluoride levels of participants.

Findings from this study are consistent with a recent Canadian study 13 of over 600 maternal-child pairs in the Calgary cohort of the Alberta Pregnancy Outcomes and Nutrition study. The study found that exposure to drinking water fluoridated at 0.7 mg/L throughout pregnancy was associated with symptoms of executive dysfunction, including poorer inhibitory control, and decreased cognitive flexibility among children aged 3 to 5 years. However, associations were most pronounced among girls. 13 Although we did not observe sex-specific associations in the current study, higher MUF SG was associated with higher symptoms of Autism Spectrum Disorder and anxiety, which are also associated with poorer cognitive flexibility. 27 - 29 Another recent study 12 conducted in the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) cohort found that higher creatinine-adjusted MUF was associated with higher scores on measures of inattention and overall ADHD symptoms from ages 6 to 12 years. While we did not find associations of MUF SG with symptoms of inattention or ADHD, this may reflect the timing of neurobehavioral assessment because symptoms of inattention are more difficult to assess (and ADHD is more difficult to diagnose) in children younger than 4 years. Although no other prospective studies, to our knowledge, have examined associations of prenatal fluoride exposure with CBCL scores, a recent cross-sectional study 30 of 12-year-old children in the Cincinnati Childhood Allergy and Air Pollution Study found that higher specific gravity-adjusted urinary fluoride levels were associated with higher somatic symptoms scores and odds of internalizing T scores being in a clinically at-risk range (defined as a T score ≥60) on the Behavior Assessment System for Children (Second Edition), particularly among boys. Still, an earlier study of 7- to 11-year-old children residing in Boston 31 found no association of dental fluorosis or environmental fluoride exposure (assessed via questionnaire) with parent-reported neurobehavioral problems on the CBCL.

Other studies conducted in Canada and Mexico have found associations of higher prenatal fluoride exposure at US-population–relevant levels with poorer neurocognitive outcomes, including lower IQ. 8 - 10 , 12 , 14 , 21 For example, a study conducted in the ELEMENT cohort found that each 0.5 mg/L increase in creatine-adjusted MUF was associated with a more than 2-point reduction in global cognitive functioning or IQ across 3 time points during middle to late childhood. 21 Similarly, research conducted in the Canadian Maternal-Infant Research on Environmental Chemicals cohort found that each 1 mg/L increase in MUF SG was associated with a 4.49-point lower IQ score in boys. 8 , 10 Taken together, the weight of the scientific literature supports an association of prenatal fluoride exposure with adverse child cognitive and neurobehavioral development in North America. Still, when considering the global body of scientific literature, there are some inconsistencies. 32 - 34

It is well-established that the prenatal and early postnatal periods are windows of susceptibility for neurodevelopmental impacts of environmental toxicant exposures. 35 , 36 Animal studies have delineated potential mechanisms underlying the association of prenatal fluoride exposure with neurobehavioral development. A 2022 study 37 found that at 90 days of age, male rats who were prenatally and perinatally exposed to relatively low fluoride levels exhibited altered neurobiochemical markers of oxidative damage, glutamate metabolism, and acetylcholinesterase activity. Another recent study 38 found that at 90 days of age, female rats exposed to low fluoride levels during gestation and lactation exhibited decreased messenger RNA expression of the α7 nicotinic acetylcholine receptor (α7nAChR) and reduced hippocampal catalase activity (an indicator of oxidative stress). Neurochemical changes observed in both studies 37 , 38 have been replicated in other animal as well as in vitro studies that included high fluoride exposures. 39 - 41 Interestingly, both oxidative stress and alterations of the α7nAChR in particular have been implicated in the pathophysiology of neurodevelopmental disorders, including Autism Spectrum Disorder. 42 , 43 Furthermore, alterations in glutamate pathways have been implicated in the cause and treatment of anxiety disorders. 44 Prenatal fluoride exposure may also adversely affect neurodevelopment and cognition by causing mitochondrial dysfunction which can increase oxidative stress, blocking autophagosome-lysosome fusion which can contribute to cellular damage, and by causing synaptic dysfunction. 45 - 47 Additionally, prenatal fluoride exposure, even at low levels, can suppress maternal thyroid gland activity which can contribute to cognitive and neurobehavioral problems in offspring. 48 , 49

There are notable strengths of the current study, including the use of individual biomarker measures of exposure assessment that provide an estimate of fluoride intake from all sources, and the adjustment for a breadth of covariates associated with fluoride exposure, metabolism, and neurodevelopment. Additionally, our study addressed a limitation of prior studies on fluoride exposure and neurodevelopment by including a sample of predominately fasting pregnant women, which can be difficult to achieve. However, there are also limitations. First, we measured fluoride in spot samples rather than 24-hour urine samples, which can be influenced by daily behaviors (eg, food and beverage consumption or use of fluoridated dental products), and therefore increase random error. Still, the inclusion of mostly fasting urine samples reduces the potential impact of food and beverage consumption on urinary fluoride concentrations. Second, we were limited in our ability to examine patterns of associations of fluoride exposure with neurobehavior according to trimester because only a subsample of participants had urine available for fluoride analyses in the first trimester and most participants did not fast prior to urine collection. Nevertheless, associations of first trimester MUF SG with CBCL scores after adjusting for blood lead were in the same direction as for the third trimester. Third, we did not have data on tap water consumption habits for the study sample; however, home cooking rates were high, and rice tended to be a dietary staple among MADRES participants, which can be a source of tap water fluoride exposure. Fourth, given that the study sample resided in Los Angeles, California, and was predominately Hispanic, we do not know whether findings observed in this study are generalizable to other US populations or are nationally representative. Fifth, this study excluded participants who delivered their babies prior to 30 weeks’ gestation which precluded examination of associations of MUF SG with neurobehavior among children who were born very preterm. Sixth, lead concentrations in whole blood were only measured for most of the study sample during the first trimester, and therefore we were only able to adjust for first trimester blood lead in our third trimester analyses. Still, we do not anticipate confounding of associations of MUF SG with CBCL scores by blood lead given that the inclusion of first trimester blood lead in first and third trimester models increased the magnitude of the associations. Furthermore, blood lead has been shown to be stable between the first and third trimesters of pregnancy, 50 which supports the use of first trimester blood lead as a proxy for third trimester blood lead.

This cohort study found that prenatal fluoride exposure was associated with increased risk for neurobehavioral problems among children residing in the US. These findings suggest that there may be a need to establish recommendations for limiting exposure to fluoride from all sources during the prenatal period, a time when the developing brain is known to be especially vulnerable to injury from environmental insults.

Accepted for Publication: March 18, 2024.

Published: May 20, 2024. doi:10.1001/jamanetworkopen.2024.11987

Corresponding Author: Ashley J. Malin, PhD, Department of Epidemiology, College of Public Health and Health Professions, University of Florida, 2004 Mowry Rd, Gainesville, FL 32603 ( [email protected] ).

Author Contributions: Dr Malin and Ms Yang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Malin, Hu, Bastain.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Malin, Eckel, Hu, Martinez-Mier, Bastain.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Malin, Eckel, Hu, Hernandez-Castro, Yang.

Obtained funding: Malin, Farzan, Habre, Breton, Bastain.

Administrative, technical, or material support: Martinez-Mier, Farzan, Habre, Bastain.

Supervision: Hu, Martinez-Mier, Farzan, Habre, Bastain.

Conflict of Interest Disclosures: Dr Hu reported having testified as a nonretained expert witness at the request of the US Department of Justice on his previously published research on the subject of prenatal fluoride exposure and neurodevelopmental outcomes as part of an ongoing trial in US District Court. Dr Farzan reported receiving grants from the National Institutes of Health outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported in part by funding from the National Institutes of Health and National Institute of Environmental Health Sciences (grant Nos. R00ES031676, ES030400, P50MD015705, P50ES026086, and R01ES021446) and the US Environmental Protection Agency (grant No. 83615801–0).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: The authors thank the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) participants, the study staff, and community clinic partners for making this work possible. The authors also thank Durdana Khan, MPH, PhD (Department of Epidemiology, University of Florida), for conducting an additional reanalysis of the data included in this study. No additional compensation was provided to Dr Khan for this task.

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Examining Urban Governance of Shrinking Cities at the National, State, and Local Level: A Comparative Case Study of Three Shrinking Cities in South Korea

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Depopulation is intensifying in non-metropolitan areas in South Korea with the nation recording a remarkably low fertility rate of 0.78 in 2022 (National Assembly Budget Office, 2023) and a significant migration trend towards metropolitan areas, especially Seoul. This migration, largely attributed to socioeconomic incentives in Seoul, has led to a situation where many describe the nation as the “Republic of Seoul” (SKKUP, 2021). Strikingly, population outflow tends to affect depopulation in non-metropolitan areas more than the birth rate decline (KRIHS, 2022). Since 2020, the population of the metropolitan areas, where it only occupies 11.8% of the total land area, has exceeded the population of the non-metropolitan areas, evidenced by an increase from 48.8% in 2000 to 50.4% in 2021 for metropolitan areas and a decrease from 51.2% in 2000 to 49.6 in 2021 for non-metropolitan areas (KRIHS 2022; KRIHS 2021). As a result, while over half of the country’s population and GDP is housed in the Seoul Metropolitan Area, 49.6% of local municipalities (113 out of 228) are facing drastic population decline (KEIS, 2022). Despite governmental interventions, regional disparities persist. This research seeks to explore sustainable strategies for the shrinking cities in South Korea by delving into three case studies with qualitative analysis of interviews with stakeholders from each municipality.

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Identifying an Area of Research

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Hilary Coombes

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You may not have a choice in what you research, it may be that you are given a particular topic area to research, or a concept to investigate. If this is the case, then if at all possible try to find some area that interests you within the given investigation. For example, let us say you are asked to research:

Why unemployment is 35% higher among unqualified people in comparison with qualified people.

Try not to fall into the trap of immediately presuming that everyone knows the answer already. If you do this, you will not only fall into a biased research outlook, but you may feel that the answer is so obvious that you are wasting your time in researching the topic. This in turn will lead you to devalue the importance of your research and you will find it extremely difficult to motivate yourself, especially if problems occur.

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Coombes, H. (2001). Identifying an Area of Research. In: Research Using IT. Palgrave Study Guides. Palgrave, London. https://doi.org/10.1007/978-1-137-05029-8_2

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