INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
www.rsisinternational.org
Page 2449
Epidemiological Trends and Diagnostic Patterns Among Clinical
Laboratories in Pangasinan
Louisa Yvette Mensah, Jonathan C. Diola
Virgen Milagrosa University Foundation, Philippines
DOI: https://dx.doi.org/10.51244/IJRSI.2025.1215PH000182
Received: 12 October 2024; Accepted: 20 October 2024; Published: 14 November 2025
ABSTRACT
This quantitative descriptive correlational research determined the epidemiological trends and diagnostic
patterns of diseases diagnosed through clinical laboratory testing in the clinical laboratories in Pangasinan over
a three-year period from 2021 to 2023.
RESULTS
show a predominance of middle-aged individuals, a slight female majority, higher income bracket, and a trend
toward urbanization among the respondents. A significant burden of chronic diseases, particularly Type 2
Diabetes and respiratory conditions, emphasizing the urgent need for targeted public health interventions and
ongoing health management strategies. The diagnostic patterns indicate a strong emphasis on essential tests for
overall health evaluation, particularly in monitoring diabetes and respiratory conditions, highlighting their
prevalence and the need for targeted medical attention. Significant relationship between demographic factors
and both the epidemiological trends and diagnostic patterns, indicating that older, higher-income females in
urban areas are particularly susceptible to various diseases and more likely to undergo comprehensive
laboratory testing. A positive correlation between epidemiological trends of various diseases and
corresponding diagnostic patterns, indicating that higher prevalence and incidence rates are associated with
increased utilization of specific clinical laboratory tests.
It is suggested that the "Action Plan - Enhancing Public Health Outcomes through Improved Epidemiological
Surveillance" be utilized to focus on the prevention and management of chronic diseases such as Type 2
Diabetes and respiratory conditions. Laboratory management should enhance protocols to ensure timely and
efficient testing for high-prevalence conditions, alongside training staff on the significance of comprehensive
testing for at-risk populations. The Department of Health is encouraged to implement community health
programs that raise awareness and provide resources for early detection and management of chronic diseases,
particularly targeting older, higher-income females. Lastly, future researchers should investigate the impacts of
socioeconomic factors on health outcomes and evaluate the effectiveness of targeted interventions in reducing
disease prevalence among vulnerable populations.
INTRODUCTION
Clinical laboratories play a vital role in the healthcare system by conducting diagnostic tests on clinical
specimens to support disease prevention, diagnosis, monitoring, and treatment. These laboratories utilize
various diagnostic tools, including molecular diagnostics, microbiological cultures, biochemical assays, and
histopathological techniques, to detect both infectious and non-communicable diseases. Globally and locally,
epidemiological trends observed in clinical laboratories help in identifying disease patterns, monitoring
outbreaks, and shaping healthcare policies. With technological advancements, these laboratories now
contribute significantly to real-time disease surveillance, antimicrobial resistance monitoring, and the
implementation of evidence-based treatment protocols.
In the Philippines, including the province of Pangasinan, both public and private clinical laboratories face the
dual burden of infectious diseases such as tuberculosis and dengue, and a growing prevalence of chronic
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
www.rsisinternational.org
Page 2450
illnesses like cardiovascular diseases, diabetes, and cancer. The country's healthcare system, a mix of public
and private sectors, is working towards expanding diagnostic capacity and improving the accuracy and
accessibility of laboratory services. In Pangasinanone of the largest provinces in Luzon with a diverse
population and healthcare access levelsprivate laboratories serve as essential healthcare providers. They
complement public health efforts by offering specialized and accessible diagnostic services that meet the
varied needs of the community.
This study on “Epidemiological Trends and Diagnostic Patterns among Clinical Laboratories in Pangasinan”
was conducted to better understand local disease prevalence and laboratory practices. By examining these
patterns, Medical Technologists can ensure that diagnostic procedures are timely, relevant, and evidence-based,
contributing to improved patient outcomes. Additionally, the study promotes continuous professional
development, enhances collaboration among healthcare stakeholders, and supports public health efforts
through accurate disease monitoring and early detection strategies. The insights gathered aim to strengthen
laboratory services in Pangasinan, aligning them with national health priorities and the Sustainable
Development Goals (SDGs), particularly in ensuring healthy lives and promoting well-being for all.
Statement of the Problem
This study primarily determined the epidemiological trends and diagnostic patterns of diseases diagnosed
through clinical laboratory testing in the clinical laboratories in Pangasinan.
Specifically, it sought to answer the following sub-problems:
What is the demographic profile of the respondents in terms of:
1. Age;
2. Sex;
3. Economic Status; and
4. Geographic Location?
What are the epidemiological trends of diseases diagnosed through clinical laboratory testing along:
1. Disease;
2. Prevalence; and
3. Incidence?
What are the diagnostic patterns of diseases diagnosed through clinical laboratory testing along:
1. Laboratory tests; and
2. Microbiological cultures?
Is there a significant relationship between the demographic profile and epidemiological trends of diseases
diagnosed through clinical laboratory testing?
1. Is there a significant relationship between the demographic profile and diagnostic patterns of diseases
diagnosed through clinical laboratory testing?
2. Is there a significant relationship between the epidemiologic trends and diagnostic patterns diagnosed
through clinical laboratory testing?
3. What Action Plan can be proposed to enhance the epidemiological and diagnostic capabilities of
clinical laboratories?
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
www.rsisinternational.org
Page 2451
RESULTS AND DISCUSSION
Demographic Profile of the Respondents
Based on age, sex, economic status, and geographic location. Further, it could be observed that according to
age distribution, the largest age group is 51-60 years (73, 27%), followed closely by 41-50 years (65, 24%),
indicating a significant proportion of middle-aged individuals. The younger age groups (21-30 and 31-40)
account for a smaller share (33, 12% and 46, 17%, respectively), while 18% (48) are above 60 years. As
regards sex, the population is slightly skewed towards females (142, 53%) compared to males (124, 47%),
suggesting a balanced representation with a slight female majority. In terms of economic status, there is a
substantial portion of the respondents that falls into the higher income bracket of more than Php 20,000 (121,
45%), while 34% (30) earn between Php 10,000-20,000, and 21% (55) are below Php10,000. This indicates a
relatively positive economic status among the majority. Lastly, as to geographic location, the majority of
respondents live in urban areas (152, 57%), compared to 43% (114) in rural locations, reflecting a trend of
urbanization in the sample.
Epidemiological Trends of Diseases Diagnosed through Clinical laboratory Testing
Type 2 Diabetes is the most prevalent condition, accounting for 21% of the population (56 cases). This
suggests a significant public health concern, indicating the need for targeted prevention and management
strategies. Chronic Bronchitis (32, 12%) and bacterial pneumonia (32, 12%) also show substantial prevalence,
highlighting respiratory conditions as critical health issues in this group. Coronary Artery Disease (CAD) (28,
11%) and Viral Pneumonia (28, 11%) follow closely, reflecting important cardiovascular and respiratory
health challenges. Myocardial Infarction (26, 10%) and Emphysema (23, 9%) are also significant, suggesting
ongoing health risks related to heart and lung conditions. Ischemic Stroke (12, 5%), Hemorrhagic Stroke (12,
5%), and Type 1 Diabetes (12,5%) are the least prevalent in this dataset. While these conditions are serious,
their lower frequency may indicate either better management or less occurrence in this population. The data
highlights a substantial burden of chronic diseases, particularly Type 2 Diabetes and respiratory illnesses. This
underscores the importance of public health Moreover, the prevalence and incidence rates of various diseases
per 1,000 population, reflecting key health concerns. Type 2 Diabetes has the highest prevalence at 6 cases per
1,000, indicating a critical health issue that may necessitate targeted public health interventions for prevention
and management. Other conditions with significant prevalence include coronary artery disease (CAD),
Myocardial Infarction, Bacterial Pneumonia, Viral Pneumonia, and Chronic Bronchitis, all at 3 cases per
1,000. This suggests these diseases are common and require ongoing health management strategies.
Also, all diseases except Type 2 Diabetes show an incidence rate of 1 new case per 1,000, indicating that new
cases are emerging at a similar rate across these conditions. This suggests a stable burden of these diseases in
the population. Type 2 Diabetes has a slightly higher incidence rate of 2, highlighting that new cases are
developing more rapidly compared to other diseases, which may indicate an increasing trend in this condition.
Diagnostic Patterns of Diseases Diagnosed through Clinical Laboratory Testing
Complete Blood Count (CBC) is the most frequently performed test, with 145 instances (55%). This suggests
it is a standard and essential test for evaluating overall health and detecting various conditions.
Lipid Profile follows closely with 96 instances (36%), indicating its importance in assessing cardiovascular
risk factors. Blood Glucose and HbA1c tests, each at 68 instances (26%), reflect a strong focus on monitoring
diabetes and metabolic health, which aligns with the prevalence of conditions like Type 2 Diabetes in the
population. Other tests like C-reactive Protein (30, 11%), Troponin Levels (26, 10%), and Coagulation Profile
(26, 10%) suggest monitoring for inflammation, cardiac events, and clotting issues, respectively.
Arterial Blood Gas tests, though less common at 23 instances (9%), indicate a need for assessing respiratory
function in specific cases.
On the other hand, as to microbial cultures, sputum cultures are the most prevalent, with 55 instances (21%),
likely reflecting a focus on respiratory infections, which are critical given the high prevalence of pneumonia
and bronchitis in the population. Blood cultures (32, 12%) are also significant, essential for identifying
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
www.rsisinternational.org
Page 2452
systemic infections or sepsis. Viral cultures (28, 11%) indicate an awareness of viral infections, which may
include respiratory viruses, aligning with the noted prevalence of viral pneumonia.
Relationship between the Demographic Profile and Epidemiological trends; and Diagnostic Patterns of
Diseases diagnosed through Clinical Laboratory Testing Epidemiological Trends
Age, sex, economic status, and geographic location are positively correlated with the frequency, prevalence,
and incidence rates of various diseases, as indicated by the Pearson r values. This correlation suggests that
older adults, particularly females with an income exceeding Php 20,000, and those residing in urban areas are
more likely to be affected by conditions such as coronary artery disease (CAD), Myocardial Infarction,
Ischemic Stroke, Hemorrhagic Stroke, Bacterial Pneumonia, Viral Pneumonia, Chronic Bronchitis,
Emphysema, Type 1 Diabetes, and Type 2 Diabetes.
Diagnostic Patterns diagnosed through Clinical Laboratory Testing
Demographic factors of age, sex, economic status, and geographic location are positively correlated with the
patterns of diseases diagnosed through clinical laboratory testing. This suggests that older adults, especially
females with an income exceeding Php 20,000, and those living in urban areas are more likely to undergo
various laboratory tests, including Lipid Profile, C-Reactive Protein, Complete Blood Count, Troponin Levels,
Blood Glucose, Coagulation Profile, Arterial Blood Gas, HbA1c, and cultures for sputum, blood, and viruses.
Relationship between the Epidemiologic Trends and Diagnostic Patterns diagnosed through Clinical
Laboratory Testing
Epidemiologic trends concerning the frequency, prevalence, and incidence rates of diseases such as Coronary
Artery Disease (CAD), Myocardial Infarction, Ischemic Stroke, Hemorrhagic Stroke, Bacterial Pneumonia,
Viral Pneumonia, Chronic Bronchitis, Emphysema, Type 1 Diabetes, and Type 2 Diabetes are positively
correlated with diagnostic patterns, including tests like Lipid Profile, C-Reactive Protein, Complete Blood
Count, Troponin Levels, Blood Glucose, Coagulation Profile, Arterial Blood Gas, HbA1c, and cultures for
sputum, blood, and viruses.
CONCLUSION
This study provides a comprehensive overview of the demographic profiles, epidemiological trends, and
diagnostic patterns observed in clinical laboratories in Pangasinan. The findings reveal critical insights into the
health challenges faced by the population and underscore the importance of targeted public health
interventions.
1. A predominance of middle-aged individuals, a slight female majority, a higher income bracket, and a
trend toward urbanization among the respondents.
2. A significant burden of chronic diseases, particularly Type 2 Diabetes and respiratory conditions,
emphasizing the urgent need for targeted public health interventions and ongoing health management
strategies.
3. The diagnostic patterns indicate a strong emphasis on essential tests for overall health evaluation,
particularly in monitoring diabetes and respiratory conditions, highlighting their prevalence and the need
for targeted medical attention.
4. Significant relationship between demographic factors and both the epidemiological trends and
diagnostic patterns, indicating that older, higher-income females in urban areas are particularly
susceptible to various diseases and more likely to undergo comprehensive laboratory testing.
5. A positive correlation between epidemiological trends of various diseases and corresponding diagnostic
patterns, indicating that higher prevalence and incidence rates are associated with increased utilization
of specific clinical laboratory tests.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
www.rsisinternational.org
Page 2453
RECOMMENDATIONS
Based on the findings of this study, several targeted recommendations are proposed to enhance public health
outcomes and improve clinical practices. These suggestions aim to address the identified health issues and
optimize the use of diagnostic resources in the region.
1. It is suggested that the "Action Plan - Enhancing Public Health Outcomes through Improved
Epidemiological Surveillance" be utilized to focus on the prevention and management of chronic diseases
such as Type 2 Diabetes and respiratory conditions.
2. Laboratory management should enhance protocols to ensure timely and efficient testing for high-
prevalence conditions, alongside training staff on the significance of comprehensive testing for at-risk
populations.
3. The Department of Health is encouraged to implement community health programs that raise awareness
and provide resources for early detection and management of chronic diseases, particularly targeting older,
higher-income females.
4. Lastly, future researchers should investigate the impacts of socioeconomic factors on health outcomes and
evaluate the effectiveness of targeted interventions in reducing disease prevalence among vulnerable
populations.
REFERENCES
1. Agrupis, K. A., Smith, C., Suzuki, S., Villanueva, A. M., Ariyoshi, K., Solante, R., Telan, E. F.,
Estrada, K. A., Uichanco, A. C., Sagurit, J., Calayo, J., Umipig, D., Dela Merced, Z., Villarama, F.,
Dimaano, E., Villarama, J. B., Lopez, E., & Sayo, A. R. (2021). Epidemiological and clinical
characteristics of the first 500 confirmed COVID-19 inpatients in a tertiary infectious disease referral
hospital in Manila, Philippines. Tropical Medicine and Health, 49(1), 48.
https://doi.org/10.1186/s41182-021-00340-0
2. Al-Qahtani, S. M., Shati, A. A., Alqahtani, Y. A., & Ali, A. S. (2022). Etiology, clinical phenotypes,
epidemiological correlates, laboratory biomarkers and diagnostic challenges of pediatric viral
meningitis: Descriptive review. Frontiers in Pediatrics, 10, 923125.
https://doi.org/10.3389/fped.2022.923125
3. Bayot, M. L., Lopes, J. E., Zubair, M., & Naidoo, P. (2024). Clinical Laboratory. National Library of
Medicine, National Center for Biotechnology Information. https://www.ncbi.nlm.nih.gov
4. Bisht, R. (2024). What is purposive sampling? Methods, techniques, and examples.
https://researcher.life
5. Brown, S., & Badrick, T. (2023). The next wave of innovation in laboratory automation: systems for
auto-verification, quality control and specimen quality assurance. Clinical Chemistry and Laboratory
Medicine, 61(1), 3743.
6. Buckee, C. (2020). Improving epidemic surveillance and response: Big data is dead, long live big data.
Elsevier Ltd. https://doi.org/10.1016/S2589
7. Caldwell, J. M., de Lara-Tuprio, E., Teng, T. R., Estuar, M. R. J. E., Sarmiento, R. F. R.,
Abayawardana, M., Leong, R. N. F., Gray, R. T., Wood, J. G., Le, L. V., McBryde, E. S., Ragonnet, R.,
& Trauer, J. M. (2021). Understanding COVID-19 dynamics and the effects of interventions in the
Philippines: A mathematical modelling study. The Lancet Regional Health Western Pacific.
https://doi.org/10.1016/j.lanwpc.2021.100211
8. CDC. (2023). Chronic disease overview. Retrieved from CDC Chronic Disease.
DOH. (2023). Epidemiology Bureau Reports. Retrieved from DOH Epidemiology Bureau.
9. Evans, A. S. (2019). Epidemiological concepts. In Bacterial infections of humans (pp. 150).
https://doi.org/10.1007/978-0-387-09843-2_1
10. Garcia, L. M., & Martinez, R. S. (2021). Parental involvement and academic achievement: A
correlational study among middle school students. Journal of Educational Psychology, 114(2), 321
335.
11. Green, E. C., Murphy, E. M., Gryboski, K., & Sweeny, K. (2020). The Health Belief Model.
https://doi.org/10.1002/9781119057840.ch68
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI | Volume XII Issue XV October 2025 | Special Issue on Public Health
www.rsisinternational.org
Page 2454
12. Johnson, C. M., & Williams, E. L. (2022). Understanding patient satisfaction in telehealth services: A
descriptive study. Journal of Telemedicine and Telecare, 28(1), 4557.
13. Kumar, R. (2024). Epidemiological challenges in India. In W. Ahrens & I. Pigeot (Eds.), Handbook of
Epidemiology. Springer. https://doi.org/10.1007/978-1-4614-6625-3_90-1
14. Lechien, J. R., & Saussez, S. (2021). Importance of epidemiological factors in the evaluation of
transmissibility and clinical severity of SARS-CoV-2 variants. The Lancet Infectious Diseases.
https://doi.org/10.1016/S1473-3099(21)00474-6
15. Lubin, I. M., Astles, J. R., Shahangian, S., Madison, B., Parry, R., Schmidt, R. L., & Rubinstein, M. L.
(2021). Bringing the clinical laboratory into the strategy to advance diagnostic excellence. Diagnosis
(Berlin), 8(3), 281294. https://doi.org/10.1515/dx-2020-0119
16. Lucero-Prisno, D. E. III, Kouwenhoven, B. N., Adebisi, Y. A., Miranda, A. V., Gyeltshen, D.,
Suleman, M. H., Chiumia, I. K., Lowe, M., Dorji, T., Huang, J., Gacutno-Evardone, A. J., Lin, X.,
Dzhusupov, K., Gacutno, K. J. A., Budhathoki, S. S., Jensen, O., Amnatsatsue, K., Sium, A. F., Ikeda,
T., & Wong, M. C. S. (2022). Top ten public health challenges to track in 2022. Public Health
Challenges. https://doi.org/10.1002/puh2.21
17. Macaranas, I. T., Notarte, K. I. R., Ver, A. T. M., Pastrana, A. M., Chua, F. J., & Sumalapao, D. E.
(2020). An epidemiological report on the burden and trend of injuries in the Philippines from 2011 to
2018. Journal of Acute Disease, 9(5), 200205. https://doi.org/10.4103/2221-6189.291284
18. Mercer, A. J. (2018). Updating the epidemiological transition model. Epidemiology and Infection,
146(6), 680687. https://doi.org/10.1017/S0950268818000572
19. Nor, F. M., Aazmi, S., Tengku Shahrul Anuar, & Azdayanti. (2023). A laboratory perspective on an
epidemiological pattern of infectious gastroenteritis: A five-year surveillance between 2016 to 2020
from established private healthcare centers within Klang Valley in Malaysia. Journal of Pure and
Applied Microbiology, 17(1). https://doi.org/10.22207/JPAM.17.1.07
20. Oltean, H. N., Allen, K. J., Frisbie, L., Lunn, S. M., Torres, L., Manahan, L., & Lindquist, S. (2023).
Sentinel surveillance system implementation and evaluation for SARS-CoV-2 genomic data,
Washington, USA, 20202021. Emerging Infectious Diseases, 29(2), 242251.
https://doi.org/10.3201/eid2902.221482
21. Smith, J. A., & Johnson, B. D. (2021). Impact of social media usage on adolescent mental health: A
quantitative study. Journal of Adolescent Psychology, 45(3), 123135.
22. Thomas, L. (2024). Clinical Laboratory Diagnostics. University Hospital Frankfurt/Main, Department
of Clinical Chemistry and Laboratory Medicine. https://www.clinical-laboratory-diagnostics.com/
23. Villalobos, A., et al. (2023). Epidemiological trends of non-communicable diseases in the Philippines:
A systematic review. Journal of Global Health, 13(1).
24. Vos, T., et al. (2023). Global Burden of Disease Study 2019: A systematic analysis for the Global
Burden of Disease Study 2019. The Lancet, 396(10258), 12031228.
25. Wang, L. P., Zhou, S. X., Wang, X., et al. (2021). Etiological, epidemiological, and clinical features of
acute diarrhea in China. Nature Communications, 12, 2464. https://doi.org/10.1038/s41467-021-22551-
z
26. Wong, C. K. H., Wong, J. Y., Tang, E. H. M., et al. (2020). Clinical presentations, laboratory and
radiological findings, and treatments for 11,028 COVID-19 patients: A systematic review and meta-
analysis. Scientific Reports, 10, 19765. https://doi.org/10.1038/s41598-020-74988-9
27. Yi, Z., Pei, S., Suo, W., Wang, X., Huang, Z., Yi, A., Wang, B., He, Z., Wang, R., Li, Y., Fan, W., &
Huang, X. (2022). Epidemiological characteristics, routine laboratory diagnosis, clinical signs and risk
factors for hand-foot-and-mouth disease: A systematic review and meta-analysis. PLoS ONE, 17(4),
e0267716. https://doi.org/10.1371/journal.pone.0267716