Vitals & Biostatistics and Computation of Data

NS-CMN II 301 Topic 15 B:Vitals & Biostatistics and Computation of Data Dr. Veena M Joseph April 19, 2025 www.gmu.ac.ae  Learning Objectives On completion of this session, the student will be able to; Define the role of Vitals and Biostatistics in C...

NS-CMN II 301 Topic 15 B:Vitals & Biostatistics and Computation of Data Dr. Veena M Joseph April 19, 2025 www.gmu.ac.ae  Learning Objectives On completion of this session, the student will be able to; Define the role of Vitals and Biostatistics in Community Health Nursing Research Enumerate and discuss the vital statistics in Community Health Nursing Understand the application of vital statistics in Community Health Nursing Enumerate and discuss the Key Statistical Methods Used in Community Health Nursing Understand the application of Biostatistics in Community Health Nursing Vital and Biostatistics in Community Health Nursing Vital and biostatistics play a crucial role in community health nursing, providing the necessary data to assess community health, identify trends, and guide evidence-based interventions. Vital Statistics provide essential data on population health status, while biostatistics enables community health nurses to analyze and interpret this data effectively. Vital statistics refer to the systematic collection, analysis, and interpretation of data related to births, deaths, marriages, and morbidity rates. These statistics are essential for tracking population health trends and developing community-based interventions. Biostatistics involves the application of statistical methods to analyze health-related data, interpret research findings, and improve community health outcomes. By incorporating these statistical approaches, community health nursing can be data-driven, proactive, and impactful in improving public health.  Key Components of Vital Statistics: 1. Birth Rate: Measures the number of live births per 1,000 people in a year. It helps in planning maternal and child health programs. 2. Death Rate (Mortality Rate): Indicates the number of deaths per 1,000 individuals per year, helping to assess the overall health status of a population. 3. Infant Mortality Rate (IMR): The number of infant deaths (under one year) per 1,000 live births, serving as a critical indicator of maternal and child health services. 4. Maternal Mortality Rate (MMR): The number of maternal deaths per 100,000 live births due to pregnancy-related causes. This is vital for evaluating maternity care services. 5. Morbidity Rate: Measures the prevalence and incidence of diseases, allowing nurses to focus on high-risk groups for targeted health interventions. Application of Vital Statistics in Community Health Nursing: Identifying high-risk populations and directing resources where needed. Monitoring trends in communicable and non-communicable diseases to design preventive programs. Planning immunization campaigns and maternal-child health services based on birth and mortality data. Methods of Computing Vital Statistics Data Vital statistics data (birth, death, morbidity, and maternal health indicators) are computed using specific formulas. a. Birth Rate Helps in planning maternal and child health services. Birth Rate = ( No of live births in a year ÷ Total population)× 1000 b. Crude Death Rate (Crude Mortality Rate) Used to assess general population health status. Crude Death Rate = (Total number of deaths in a year ÷ divided by Total live births in a year ) × 1000 c. Infant Mortality Rate (IMR) Indicates quality of neonatal and maternal care. IMR = (No of infant deaths < 1 year ÷ Total live births in a year ) × 1000 d. Maternal Mortality Rate (MMR) Measures effectiveness of maternal health services. MMR =( No of maternal deaths due to pregnancy related causes ÷ Total live births in a year )× 1000 e. Morbidity Rate (Disease Prevalence/Incidence) Helps in disease control and prevention planning. Incidence Rate = ( New cases of a disease in a specific period ÷ Total at risk population) × 1000. Prevalence Rate = (Total cases including New and Existing ÷ Total population) × 1000 Methods of Computing Biostatistical Data Computing data in community health nursing relies on mathematical formulas and statistical tools to analyze vital statistics and biostatistics. These methods help in tracking health trends, evaluating interventions, and Descriptive Statistics Used to summarize and describe health data. A. Descriptive Statistics Used to summarize and describe health data. Mean (Average): Mean= (Sum of all values divided by total number of values) Median: The middle value when data is arranged in ascending order. Mode: The most frequently occurring value. Standard Deviation (SD): Measures data dispersion around the mean. B. Inferential Statistics Used to draw conclusions about a population from a sample. Chi-Square Test (χ²): Determines associations between categorical variables (e.g., does smoking influence pregnancy outcomes?). T-Test: Compares two group means to find statistical differences. Correlation & Regression Analysis: Examines relationships between variables (e.g., impact of maternal diet on birth weight). c. Epidemiological Measures Relative Risk (RR): Assess the strength of association between exposure and disease Measures risk of disease due to exposure, e.g., diabetes in pregnant women. RR=(Incidence rate in exposed group ÷ Incidence rate in unexposed ) Odds Ratio (OR): Used in case-control studies to assess disease  Recommended Reading Park K. Textbook of Preventive and Social Medicine. 24th ed. India: Bhanot Publishers; 2017. pp. 876-880. Stanhope M,Lancaster J.Public health nursing.9th ed.Elsevier ISBN 978- 032-3321-532 pg 587-588