Health Research Methods Analytical Survey

Health Research Methods

An analytical survey is a survey or research that tries to explore how and why health phenomena occur. Then conduct an analysis of the dynamics of correlation between phenomena or between risk factors and Effect Factors. The effect factor is a result of the existence of risk factors, while the risk factor is a phenomenon that results in the occurrence of effects (steering). Smoking is a risk factor for the occurrence of lung cancer (effects). Hypertension is one of the risk factors for heart disease (effects).

In research (survey) analytics, from correlation analysis can be known how far the contribution of certain risk factors to the existence of a particular event (effect). Broadly speaking, these analytical surveys are divided into three approaches (types), namely cross-sectional analytical surveys, case-control analytical surveys (retail; respective), and cohort analytical surveys (prospective).

1. Cross-Sectional Survey Design

A cross-sectional survey is a study to study the dynamics of correlation between risk factors with effects, by 

approach, observation, or data collection at once at a time (point in time approach). That is, each research subject was observed only once and measurements were made of the character status or subject variables at the time of examination. This does not mean that all research subjects were observed at the same time. Cross-sectional research is often also called transversal research and is often used in epidemiological studies. Compared to other studies, this research method is the weakest because this study is the easiest to do and very simple. Definitions that need to be understood in cross-sectional research, and also for other types of analytical research in the field of public health, including:

  1. illness or health problem, or effect.
  2. risk factors for the occurrence of the disease, namely the factors causing the disease or health problems.
  3. disease agent (cause of disease).

Risk factors are factors or conditions that affect the development of a particular disease or health status. There are two kinds of risk factors, namely

2. Risk factors are derived from the organism itself (intrinsic risk factors). 

These intrinsic risk factors are distinguished into:

  • Sex and age factors

Certain diseases are related or tend to be suffered by someone of a certain gender or age. For example, gastritis, tend to be suffered by men more than women. Cardiovascular tends to be suffered by or; ing aged over 40 years.

  • Specific anatomical or constitutional factors

There are certain parts of the body that are sensitive to disease. For example, the herpes virus which attacks the nerves.

  • Nutritional factors

A person who suffers from malnutrition (malnutrition) will be susceptible to infectious diseases, especially pulmonary tuberculosis and diarrhea.

3. Risk factors derived from the environment (extrinsic risk factors) 

By type, these extrinsic factors can be physical, chemical, biological, psychological, socio-cultural, and behavioral states. For example, the state of densely populated villages is a risk factor for acute respiratory tract infections (Ari). People who work in enterprises that use certain chemicals are at risk for diseases caused by those chemicals. The situation is rowdy, full of opposition, hostility, and so on, which is a risk factor for people with stress.

Risk factors are different from the agent (cause of the disease). Disease agents are micro-organisms or environmental conditions that react directly to an individual so that the individual becomes ill. The agent is a factor that must exist for the occurrence of the disease. While the risk factor is a condition that allows the mechanism of the relationship between the agent of the disease with the host (host) and the human host so that the effect (pain). For example, Bacillus mycobacterium is the “agent” of tuberculosis Meanwhile, poor environmental conditions, densely populated houses, without ventilation, and dampness, are risk factors for the contact between the mycobacterium and people, resulting in an effect (illness). 

As mentioned earlier, cross-sectional survey research is a study in which variables including Risk Factors and variables including effects are observed at the same time. Therefore, the design (design) of this study can be described as follows:

From the above design scheme, it can be concluded that the steps of cross-sectional research are as follows

  1. Identify research variables and identify risk factors and Effect Factors.
  2. Establish the research subject or population and sample.
  3. Observation or measurement of variables that are risk factors and effects at the same time based on the state of the variables at the time (data collection).
  4. Perform correlation analysis by comparing the proportion between groups of observations (measurements).

Simple example: want to know the relationship between Iron anemia in pregnant women with baby birth weight (BBL), using the design or cross-sectional approach.

First stage:

  1. Identify the variables to be studied and the position of each:
  2. Dependent variable (effect): BBL.
  3. Independent variable (risk): iron anemia.

Independent variables (risk) are controlled: parity, maternal age, pregnancy care, and so on, grouped as confounding variables (confounding variables).

Second stage: 

Establish the subject of the study or population and its sample. The research subjects here are clearly new mothers but need to be limited from which areas they will be taken, whether the scope of the General Hospital, Maternity Hospital, or maternity hospital or in the community within the scope of the village, village or district. Similarly, the time limit is also determined. Then how to take the sample, whether based on random or nonrandom techniques.

The third stage: 

Data collection, observation, or measurement of the dependent variable, independent, and controlled variables simultaneously (at the same time). The trick, measuring the weight of the baby born, checking the mother's blood Hb, asking age, parity, and other control variables.

The fourth stage 

Is processing and analyzing data by comparing BBL and Hb maternal blood. From this analysis will be obtained evidence of the presence or absence of a relationship between anemia and BBL.

As mentioned earlier, this research design has advantages: easy to implement, simple, economical in terms of time, and the results can be obtained quickly. In addition, at the same time can be collected many variables, both risk variables, and effect variables. However, this design has limitations such as:

  1. A large research subject is required.
  2. Can not accurately describe the development of the disease.
  3. It is not valid to predict a trend.
  4. The correlation of risk factors with effect factors was weakest when compared with the other two cross-sectional study designs.


Notoatmodjo, S. (2010). Notoatmodjo s Health Research Methodology, editor. Jakarta: PT. Rineka Cipta.
Creswell, J.W., & Miller, D. (2000). Determining validity in qualita¬tive inquiry. Theory into Practice, 39(3), 124-130.
Bowling, A. (2014). Research methods in health: investigating health and health services. McGraw-hill Education (UK).
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approach. Sage publications.
Creswell, J.W. & Piano Clark, V.L. (2007). Designing and Conducting Mixed Methods Research. Thousand Oaks, CA: Sage.
Green, J., & Thorogood, N. (2018). Qualitative methods for health research. sage.

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