Epidemiological Methods

1. INTRODUCTION TO
RESEARCH DESIGNS IN
PUBLIC HEALTH
Augustine Gatimu Njuguna ,PhD (Epidemiology) Candt-JKUAT
,FUoN (Epidemiology) – UoN FUoN (Health Informatics) – UoN
MSc - Biostatistics – UoN BSc-Nursing – KeMU

2. PRESENTATION OUTLINE
INTRODUCTION
• What is a Research Design?
• Types of Research Designs
• Observational Studies
• Experimental Studies
• Randomized Controlled Trials
• Cohort Studies
• Case-Control Studies
• Cross-Sectional Studies
• Systematic Reviews
• Meta-Analyses
• Bias in Research Designs
• Ethical Considerations
• Sample Size and Power
• Data Collection and Analysis
• Validity and Reliability
• Statistical Methods
• Reporting Results
• Interpreting Results
• Limitations and Future Directions
• Conclusion
• References

3. INTRODUCTION
• Welcome to this presentation on research designs in public health.
• Research designs are critical to understanding the impact of interventions and policies on
populations, and can help inform decision-making at all levels of society.
• In this presentation, we will explore the different types of research designs used in public
health, from observational studies to randomized controlled trials.
• We will also discuss the importance of ethical considerations, sample size and power, data
collection and analysis, validity and reliability, statistical methods, and reporting and
interpreting results accurately.
• By the end of this presentation, you will have a better understanding of the role that
research designs play in public health and why they matter.

4. WHAT IS A RESEARCH DESIGN?
• A research design is the plan or blueprint for a study that outlines the structure, methods, and
procedures used to collect and analyze data.
• It is important to have a well-designed study because it ensures that the research is conducted
in a systematic and rigorous manner, and that the results are reliable and valid.
• In public health, research designs are used to investigate a wide range of topics, including
disease prevention, health promotion, and health policy.
• For example, a researcher may use a randomized controlled trial to evaluate the effectiveness
of a new vaccine, or a cohort study to examine the long-term health effects of exposure to
environmental toxins.
• By using appropriate research designs, researchers can generate evidence that informs public
health practice and policy.

5. TYPES OF RESEARCH DESIGNS
• Research designs are the blueprint for any study, and they determine how data is collected, analyzed, and
interpreted.
• In public health research, there are two main types of designs: observational and experimental.
• Observational studies are used to observe and describe a population without manipulating any variables.
• Examples include cross-sectional studies and cohort studies.
• On the other hand, experimental studies involve manipulating one or more variables to see their effect on an
outcome.
• Randomized controlled trials are considered the gold standard in experimental studies.
• Observational studies are useful when it is not possible or ethical to manipulate variables, but they have
limitations.
• For example, they cannot establish causality because there may be confounding factors that influence the
outcome.
• Experimental studies, on the other hand, can establish causality, but they are expensive and time-consuming.
• It is important to choose the appropriate design based on the research question and available resources.

6. OBSERVATIONAL STUDIES
• Observational studies are an important type of research design used in public health.
• They involve observing and analyzing the behavior or health outcomes of a group of
individuals without manipulating any variables.
• One advantage of observational studies is that they can be conducted in real-world settings,
making them more applicable to everyday life.
• However, one disadvantage is that they cannot establish causality, meaning they cannot
determine whether a certain exposure caused a particular outcome.
• For example, a study may observe that people who eat more fruits and vegetables have lower
rates of heart disease, but it cannot prove that the fruits and vegetables caused the lower rates
of heart disease.

7. OBSERVATIONAL STUDIES CONT’D
• Despite their limitations, observational studies have been used successfully in public health
research.
• One example is the Framingham Heart Study, which began in 1948 and has followed
generations of participants to identify risk factors for heart disease.
• Another example is the Nurses' Health Study, which began in 1976 and has provided valuable
insights into the role of diet and lifestyle in preventing chronic diseases.
• By carefully designing and conducting observational studies, researchers can gain valuable
insights into the health of populations and identify potential risk factors for disease.

8. EXPERIMENTAL STUDIES
• Experimental studies are research designs that involve the manipulation of one or
more variables to determine their effect on an outcome.
• They are often used in public health research to test the efficacy of interventions or
treatments.
• One advantage of experimental studies is that they allow researchers to establish
cause-and-effect relationships between variables.
• However, they can also be expensive and time-consuming to conduct, and there may
be ethical concerns about manipulating variables in human subjects.
• Examples of experimental studies in public health include randomized controlled
trials of new vaccines or medications.

9. RANDOMIZED CONTROLLED TRIALS
• A randomized controlled trial (RCT) is a type of study design used in public health research
that involves randomly assigning participants to either an intervention group or a control
group.
• The intervention group receives the treatment or intervention being studied, while the
control group does not.
• By randomly assigning participants, researchers can ensure that any differences observed
between the two groups are due to the intervention and not to other factors.

10. RANDOMIZED CONTROLLED TRIALS
CONT’D
• RCTs are considered the gold standard in public health research because they
provide the strongest evidence for causality.
• They allow researchers to control for confounding variables and to make causal
inferences about the relationship between the intervention and the outcome.
• Some examples of RCTs in public health include studies on the effectiveness of
vaccines, medications, and behavioral interventions.

11. COHORT STUDIES
• A cohort study is a type of observational study that follows a group of people over time to see
how various factors, such as lifestyle choices or exposure to environmental toxins, affect their
health outcomes.
• Cohort studies are often used in public health research because they can provide valuable
information about the causes and risk factors for various diseases.
• One example of a cohort study is the Nurses' Health Study, which began in 1976 and has
followed over 100,000 female nurses in the United States.
• This study has provided important insights into the risk factors for breast cancer, heart disease,
and other conditions.
• Another example is the Framingham Heart Study, which began in 1948 and has followed three
generations of participants to better understand the causes of cardiovascular disease.

12. CASE-CONTROL STUDIES
• A case-control study is a type of observational study that compares individuals with a particular
health outcome (the cases) to individuals without the outcome (the controls).
• The goal of this study design is to identify factors that may be associated with the development of
the health outcome.
• Case-control studies are often used when studying rare diseases or conditions, as they allow
researchers to efficiently examine potential risk factors.
• In a case-control study, participants are selected based on their disease status (case or control)
and then asked about their exposure to various risk factors.
• The results are then analyzed to determine if there is an association between the exposure and
the disease.
• While case-control studies can provide valuable insights into potential risk factors for a disease,
they are not able to establish causality.
• Additionally, there may be issues with recall bias or selection bias in these types of studies.

13. CROSS-SECTIONAL STUDIES
• Cross-sectional studies are a type of observational study that involve collecting data from
a sample of individuals at a single point in time.
• These studies are often used to estimate the prevalence of a disease or health condition
within a population, as well as to identify risk factors associated with the condition.
• One example of a cross-sectional study is the National Health and Nutrition Examination
Survey (NHANES), which collects data on the health and nutritional status of adults and
children in the United States.
• This survey has been used to track trends in obesity, diabetes, and other health conditions
over time, as well as to identify risk factors for these conditions.

14. SYSTEMATIC REVIEWS
• A systematic review is a type of research study that involves a comprehensive and thorough
analysis of all available evidence on a particular topic.
• This includes searching for and reviewing all relevant studies, assessing their quality and
bias, and synthesizing the results to draw conclusions about the overall state of knowledge
on the topic.
• Systematic reviews are particularly useful in public health research because they can help
identify gaps in knowledge, highlight areas where more research is needed, and inform
policy and practice decisions based on the best available evidence.
• For example, a systematic review of studies on the effectiveness of smoking cessation
interventions might reveal which interventions are most effective and which populations are
most likely to benefit from them.

15. META-ANALYSES
• A meta-analysis is a statistical method used to combine the results of multiple studies on a
particular topic.
• By pooling data from several studies, researchers can gain a more comprehensive
understanding of the subject and increase the statistical power of their analysis.
• Meta-analyses are commonly used in public health research to synthesize findings from
multiple studies and draw more robust conclusions.
• Meta-analyses can be particularly useful when individual studies have produced
conflicting or inconclusive results.
• By combining data from all available studies, researchers can identify patterns and trends
that might not be apparent in any single study.
• However, it's important to note that meta-analyses are only as good as the studies they
include.
• If the studies have significant methodological flaws or biases, the results of the meta-
analysis may be compromised.

16. BIAS IN RESEARCH DESIGNS
• Bias is an inherent risk in any research design, and it can have a significant impact on the
validity of study results.
• There are several types of bias that can occur in research designs, including selection bias,
measurement bias, and confounding.
• Selection bias occurs when study participants are not representative of the population being
studied, while measurement bias occurs when the methods used to measure outcomes are
inaccurate or unreliable.
• Confounding occurs when there are other factors that could be influencing the outcome
being studied that are not accounted for in the study design.

17. BIAS IN RESEARCH DESIGNS CONT’D
• To minimize bias in research designs, it is important to carefully consider the study population,
use valid and reliable measures, and control for confounding variables.
• For example, in a study looking at the effectiveness of a new drug, researchers might randomly
assign participants to either the treatment group or a control group to ensure that both groups
are similar in terms of baseline characteristics.
• They might also use blinding techniques to ensure that neither the participants nor the
researchers know which group the participant is in, which can help reduce measurement bias.
• By taking steps to minimize bias, researchers can increase the likelihood that their study
results accurately reflect the true effects of the intervention being studied.

18. ETHICAL CONSIDERATIONS
• When conducting research in public health, it is essential to take into account the ethical
considerations that come with the territory.
• These considerations include ensuring that participants are fully informed about the study
and its potential risks and benefits, obtaining their voluntary consent to participate, and
protecting their privacy and confidentiality throughout the study.
• Moreover, researchers must also consider the potential for harm to vulnerable populations,
such as children or those with mental or physical disabilities, and take steps to minimize this
risk.
• Additionally, they must ensure that the study is designed in a way that minimizes any potential
conflicts of interest and that the results are reported accurately and transparently.

19. SAMPLE SIZE AND POWER
• Sample size and power are critical components of research designs in public health.
• Sample size refers to the number of participants in a study, while power refers to the ability of a
study to detect a significant effect if one exists.
• Having an adequate sample size and power can greatly impact the validity of study results.
• For example, a study on the effectiveness of a new medication may have inconclusive results if
the sample size is too small or the power is too low.
• On the other hand, a study with a large sample size and high power can provide more reliable
and generalizable results.
• It is important for researchers to carefully consider sample size and power when designing
their studies.

20. DATA COLLECTION AND ANALYSIS
• In public health research, data collection and analysis are critical components of a well-
designed study.
• There are various methods of data collection, including surveys, interviews, and observations,
each with its own advantages and disadvantages.
• Surveys, for example, can collect a large amount of data quickly and efficiently, but may suffer
from response bias.
• Interviews, on the other hand, can provide more detailed information but may be time-
consuming and costly.
• Observations can provide valuable insights into behavior, but may not be feasible for certain
populations or settings.

21. DATA COLLECTION AND ANALYSIS CONT’D
• Once data is collected, it must be analyzed using appropriate statistical methods.
• Descriptive statistics can be used to summarize the data, while inferential statistics can be used
to make predictions or test hypotheses.
• However, the choice of statistical method depends on the type of data collected and the
research question being addressed.
• For example, regression analysis can be used to examine the relationship between two
variables, while survival analysis can be used to analyze time-to-event data.
• It is important to choose the appropriate statistical method to ensure accurate and meaningful
results.

22. VALIDITY AND RELIABILITY
• Validity and reliability are two important concepts in research designs that can greatly
impact the results of a study.
• Validity refers to the accuracy of a measurement or instrument, while reliability refers to the
consistency of the measurement or instrument over time or across different researchers.
• If a study has low validity or reliability, the results may not accurately reflect the phenomenon
being studied.
• For example, in a study on the effectiveness of a new medication for a particular disease, if
the measurement of the disease severity is not valid, the study may not accurately show the
true effects of the medication.
• Similarly, if the measurement of disease severity is not reliable, the results may vary widely
depending on who is measuring it or when it is measured.
• Therefore, ensuring high levels of validity and reliability is critical for producing accurate
and meaningful results in public health research.

23. STATISTICAL METHODS CONT’D
• Statistical methods play a critical role in public health research.
• They allow researchers to analyze data and draw conclusions about the relationships between
variables.
• Some common statistical methods used in public health research include regression analysis,
survival analysis, and time series analysis.
• Each statistical method has its own advantages and disadvantages.
• For example, regression analysis is useful for examining the relationship between two or more
variables, but it can be sensitive to outliers.
• Survival analysis is useful for studying time-to-event data, but it assumes that the hazard rate is
constant over time.
• Time series analysis is useful for studying trends over time, but it can be difficult to determine
causality.

24. STATISTICAL METHODS
• To illustrate the use of different statistical methods in public health research, one study found
that regression analysis was used to examine the relationship between body mass index
(BMI) and the risk of developing type 2 diabetes.
• Survival analysis was used to examine the time to relapse after addiction treatment.
• Time series analysis was used to examine the impact of air pollution on asthma
hospitalizations over time.

25. REPORTING RESULTS
• Reporting results accurately and transparently is crucial in public health research as it ensures that
the findings are reliable and can be replicated.
• It also allows other researchers to build upon the findings and contribute to the advancement of
knowledge in the field.
• Inaccurate or incomplete reporting can lead to misinterpretation of results, which can have serious
consequences for public health interventions.
• One example of the importance of accurate reporting is the case of a study on the effectiveness of a
new drug for treating a particular disease.
• The initial publication of the study suggested that the drug was highly effective, but subsequent
investigations revealed that the study had not reported all of the data and had excluded certain
patients from the analysis.
• When the full data set was analyzed, it became clear that the drug was not as effective as initially
reported.
• This highlights the importance of transparency in reporting results and the need for peer review to
ensure the accuracy of findings.

26. INTERPRETING RESULTS
• Interpreting results accurately and objectively is crucial in public health research.
• It involves analyzing the data collected during a study and drawing conclusions that are
supported by the evidence.
• This process requires careful attention to detail and an understanding of statistical methods, as
well as an awareness of potential biases that may affect the results.
• One example of the importance of accurate interpretation of results is the case of a study that
found a correlation between coffee consumption and lower risk of certain types of cancer.
• While this result was initially celebrated, further analysis revealed that the correlation was likely
due to confounding factors such as smoking and alcohol consumption.
• Without careful interpretation of the data, researchers could have drawn incorrect conclusions
and potentially misled the public about the health benefits of coffee.

27. LIMITATIONS AND FUTURE DIRECTIONS
• While research designs in public health have greatly advanced our understanding of
disease and prevention, there are still limitations to these approaches.
• One limitation is the potential for bias in study design or data collection, which can impact
the validity of results.
• Future research should focus on minimizing bias through rigorous study design and
transparent reporting.
• Another limitation is the difficulty in generalizing findings from one population to another.
• This is particularly relevant for studies conducted in low- and middle-income countries,
where access to healthcare and other resources may be limited.
• Future research should aim to address these disparities and develop interventions that are
effective across diverse populations.

28. CONCLUSION
• In conclusion, we have explored the various types of research designs used in public health,
including observational and experimental studies.
• We have discussed the advantages and disadvantages of each type of study, as well as the
importance of ethical considerations, sample size and power, data collection and analysis,
validity and reliability, statistical methods, and accurate reporting and interpretation of results.
• It is clear that research designs play a critical role in public health, as they enable us to gather
reliable and valid data that can inform policy and practice.
• By conducting well-designed studies, we can better understand the complex health
challenges facing our communities and develop effective interventions to address them.
• As such, it is essential that we continue to invest in research designs and support the work of
public health researchers around the world.

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