Here are all 11 answers from Park's Textbook of Preventive and Social Medicine (pages 944-1027), with Park's own diagrams included:
BIOSTATISTICS & HEALTH INFORMATION - SAQ Answers (8 Marks Each)
Q1. Define Health Information and Biostatistics
HEALTH INFORMATION
- Data = discrete observations that carry little meaning alone.
- Information = data transformed by reducing, summarizing, and adjusting it (for age, sex variations) so comparisons across time and place are possible.
- Intelligence = information further transformed through integration with experience, social and political values, to guide decision-makers.
"Data that are not transformed into information, and information that is not transformed into intelligence to guide decision-makers...are of little value." - Park
BIOSTATISTICS (definition)
Biostatistics is the application of statistical methods to biological and medical data. It includes the collection, classification, analysis, and interpretation of data relating to health and disease in populations.
Uses of Health Information (Park):
- To measure health status and quantify health problems
- For local, national and international comparisons
- For planning, administration and management of health services
- For assessing effectiveness and efficiency of health services
- For assessing attitudes and satisfaction of beneficiaries
- For research into health and disease problems
Requirements of a Health Information System (WHO):
- Should be population-based
- Should avoid unnecessary agglomeration of data
- Should be problem-oriented
- Should employ functional and operational terms
- Should express information briefly and imaginatively (tables, charts, %)
- Should provide for feedback of data
Components of HIS:
- Demography and vital events
- Environmental health statistics
- Health status - mortality, morbidity, disability, quality of life
- Health resources - facilities, beds, manpower
- Utilization of health services
- Indices of outcome of medical care
- Financial statistics
Q2. Sources of Health Information ****
Park lists 14 sources:
- Census - decennial counting of population
- Registration of Vital Events - continuous record of births and deaths
- Sample Registration System (SRS) - dual-record system for birth/death rates
- National Sample Survey - periodic surveys on health, income, expenditure
- Health Surveys - e.g., National Family Health Survey (NFHS)
- Hospital Records - clinical data, morbidity, procedures
- Disease Notification - compulsory notification of communicable diseases
- Epidemiological Surveillance - monitoring of disease patterns
- Records of Health Services - PHC records, immunization coverage
- Research Studies - cohort, case-control, randomized trials
- Medical Certification of Cause of Death
- National Health Profile - compiled by CBHI
- Other Routine Statistics - demographic, economic, social security
- Non-quantifiable Information - policies, legislation, public attitudes
"The lifeblood of a health information system is the routine health statistics." - Park
Q3. Census in India ********
Definition (UN): "The total process of collecting, compiling and publishing demographic, economic and social data pertaining at a specified time or times, to all persons in a country or delimited territory."
Key Facts about Indian Census:
- First regular census: 1881
- Conducted every 10 years
- Last census held: March 2011
- Usually conducted at end of first quarter (most people are at their homes)
- Legal basis: Census Act of 1948
- Supreme officer: Census Commissioner for India
Primary Functions:
- Total count of population
- Age and sex distribution
- Social and economic characteristics
- Conditions of living, income, literacy
Importance:
- Provides base data for computing vital statistical rates
- Provides frame of reference for planning, action and research
- Without census data, quantified health, demographic and socio-economic indicators cannot be obtained
Drawback: Full results are usually not available quickly (takes several years to analyse)
Q4. Sample Registration System (SRS) ***
Why SRS? Civil registration is deficient in India - data deficient in accuracy, timeliness, completeness.
Origin: Initiated in the mid-1960s to provide reliable estimates of birth and death rates at National and State levels.
Nature: A dual-record system consisting of:
- Continuous enumeration of births and deaths by an enumerator
- Independent survey every 6 months by an investigator-supervisor
The half-yearly survey:
- Acts as independent check on events recorded by enumerator
- Produces denominator required for computing rates
Coverage: Now covers the entire country.
Importance:
- Major source of health information in India
- Provides Crude Birth Rate (CBR), Crude Death Rate (CDR), Infant Mortality Rate (IMR)
- Since introduction, shows steady decline in birth rate, death rate, and IMR
Q5. Civil Registration System (CRS) ***
Definition (UN): "Legal registration, statistical recording and reporting of the occurrence of, and the collection, compilation, presentation, analysis and distribution of statistics pertaining to vital events - i.e., live births, deaths, foetal deaths, marriages, divorces, adoptions, legitimations, recognitions, annulments and legal separations."
History in India:
- India has a long tradition of registration of births and deaths
- Individual States like Tamil Nadu, Karnataka, Assam passed their own Acts
- Registration was voluntary until 1969
Problems with Civil Registration in India:
- Illiteracy, ignorance
- Lack of concern and motivation
- Lack of uniformity in collection, compilation and transmission
- Different systems for rural and urban areas
- Multiple registration agencies (health, panchayat, police, revenue)
The Central Births and Deaths Registration Act, 1969:
- Came into force: 1 April 1970
- Provides for compulsory registration of births and deaths throughout India
- Ensures uniformity and comparability of data
- Time limit for registration: 21 days uniformly across India
- Late fee imposed for default
- From October 2018: Aadhaar number mandatory for death registration
- Responsibility: Parents/relatives for home events; Heads of hospitals/nursing homes for institutional events
Lay Reporting: Village health guides collect and record vital events at community level - first-line approach in countries with incomplete registration systems.
Q6. Types of Data Presentation
"Statistical data, once collected, must be arranged purposively, in order to bring out the important points clearly and strikingly." - Park
Methods:
1. TABULATION
- Devices for presenting data from masses of statistical material
- First step before analysis or interpretation
- Types: Simple tables and Frequency distribution tables
Principles of a good table:
(a) Tables should be numbered
(b) Brief, self-explanatory title
(c) Clear, concise column/row headings
(d) Data presented by size, chronologically, alphabetically or geographically
(e) Percentages and averages placed close for comparison
(f) No table should be too large
(g) Vertical arrangement preferred over horizontal
(h) Footnotes where necessary
2. BAR CHARTS
FIG. 1 - Simple Bar Chart: India Sex Ratio 1901-2011
FIG. 2 - Horizontal Bar Chart: Mean age at marriage (Females)
(a) Simple Bar Chart - Vertical or horizontal; bars proportional to magnitude
(b) Multiple Bar Chart - Two or more bars grouped together for comparison
FIG. 3 - Multiple Bar Chart: Population and land area by Region
(c) Component Bar Chart - Bars divided into parts representing items
FIG. 4 - Component Bar Chart: India Growth of Population 1901-2011
3. HISTOGRAM
A pictorial diagram of frequency distribution. Class intervals on horizontal axis, frequencies on vertical axis. Area of each block is proportional to frequency.
FIG. 5 - Histogram: Frequency distribution of diastolic BP in females aged 45-64 years
4. FREQUENCY POLYGON
Obtained by joining mid-points of histogram blocks.
FIG. 6 - Frequency Polygon: Distribution of systolic BP readings in a community
5. LINE DIAGRAM
Used to show trend of events over time.
FIG. 7 - Line Diagram: Malaria cases reported 1971-1978
6. PIE CHART (Sector Diagram)
Areas of segments of a circle are compared. Percentages indicated in segments.
FIG. 8 - Pie Chart: World Population - Developed (26%) vs Developing (74%) Countries
7. PICTOGRAM
Small pictures/symbols used to present data to general public. Example: doctor figure representing population per physician.
FIG. 9 - Pictogram: Population per physician
8. SCATTER DIAGRAM
Shows relationship between two variables. If dots cluster around a straight line - evidence of linear relationship.
FIG. 10 - Scatter Diagram: Fat intake vs Sugar intake in 41 countries (positive correlation)
9. STATISTICAL MAPS
Used when data refers to geographic areas. Types:
- Shaded maps - areas shaded with different colours/intensities
- Dot maps
Q7. Sampling Methods ***
Definition of Sampling:
"When a large proportion of individuals or items have to be studied, we take a sample. It is easier and more economical to study the sample than the whole population or universe."
Sampling Frame: A listing of all members of the universe from which the sample will be drawn. Its accuracy and completeness influences the quality of the sample.
Three most commonly used methods (Park):
(1) Simple Random Sample
- Each unit is assigned a number
- A table of random numbers is used to select units
- Each unit has equal chance of being selected
- Provides greatest number of possible samples
- Eliminates personal selection and unconscious bias
(2) Systematic Random Sample
- Pick every 5th or 10th unit at regular intervals
- Example: For a 10% filaria survey, houses are numbered, then every 10th house is selected
- Simple and easy to execute
(3) Stratified Random Sample
- Population is divided into strata (e.g., age groups, socioeconomic status)
- Random sample drawn from each stratum
- Ensures representation from all subgroups
- More precise than simple random sampling
Other methods mentioned by Park:
- Cluster sampling - geographic clusters selected; all in cluster studied
- Multistage sampling - sampling done in stages (district → village → household)
- Purposive (judgement) sampling - investigator selects "typical" units
- Quota sampling - fixed number from each category
Q8. Normal Distribution Curve ***
Definition:
The normal distribution (Gaussian distribution) is a symmetrical, bell-shaped curve where:
- Mean = Median = Mode (all coincide at the centre)
- The curve is symmetric about the mean
- Tails extend to infinity in both directions
Properties (Park's Table):
| Relative Deviate (z) = (x - x̄)/σ | Proportion of area from middle |
|---|
| 0.00 | 0.0000 |
| 0.50 | 0.1915 |
| 1.00 | 0.3413 |
| 1.50 | 0.4332 |
| 2.00 | 0.4772 |
| 3.00 | 0.4987 |
| 4.00 | 0.49997 |
Key proportions:
- ±1 SD covers 68.27% of all observations (2 × 0.3413 = 68.27%)
- ±2 SD covers 95.44% of all observations (2 × 0.4772 = 95.44%)
- ±3 SD covers 99.73% of all observations (2 × 0.4987 = 99.73%)
Formula for Relative Deviate:
z = (x - x̄) / σ
Example from Park:
Pulse of normal males = 72, SD = 2. Probability that a male has pulse of 80 or more?
z = (80 - 72) / 2 = 4
Area = 0.49997; Probability beyond this = 0.5 - 0.49997 = 0.00003
Only 3 out of 1,00,000 individuals would likely have pulse rate of 80 or higher.
Uses:
- Basis for many statistical tests
- Calculation of probability
- Setting reference ranges in clinical medicine
Q9. Measures of Central Tendency **** (Mean, Median, Mode)
"The word 'average' implies a value in the distribution around which the other values are distributed." - Park
Three types:
(1) THE MEAN (Arithmetic Mean)
- Denoted by x̄ ("X bar")
- Formula: x̄ = Σx / n (sum of all observations ÷ number of observations)
- 'Σ' denotes summation; 'n' denotes number of observations
Example (Park): Diastolic BP of 10 individuals = 83, 75, 81, 79, 71, 95, 75, 77, 84, 90
- Total = 810; Mean = 810 ÷ 10 = 81.0
Advantages: Easy to calculate and understand
Disadvantages: Unduly influenced by extreme (abnormal) values
(2) THE MEDIAN
- Middle value when data arranged in ascending or descending order
- If odd number of values: middle value is median
- If even number of values: average of two middle values
Example (Park - odd, 9 values):
Data arranged in order: 71, 75, 75, 77, 79, 81, 83, 84, 95
Median = 79 (middle value)
Example (Park - even, 10 values):
71, 75, 75, 77, 79, 81, 83, 84, 90, 95
Median = (79 + 81) / 2 = 80
Advantage: Not affected by extreme values
Disadvantage: Does not use all values in computation
(3) THE MODE
- The value that occurs most frequently in a distribution
- Example: In a series 3, 5, 7, 7, 7, 9, 10 - Mode = 7
- A distribution may be unimodal, bimodal, or multimodal
Comparison:
| Feature | Mean | Median | Mode |
|---|
| Definition | Sum ÷ number | Middle value | Most frequent value |
| Affected by extremes | Yes | No | No |
| Uses all values | Yes | No | No |
| Best used when | Normal distribution | Skewed data | Categorical/discrete data |
Q10. Measures of Deviation **** (Range, Mean Deviation, Standard Deviation)
Measures of deviation (dispersion) indicate how far the individual observations are scattered around their average.
(a) RANGE
- Simplest measure of dispersion
- Difference between highest and lowest values
- Example: BP values - 83, 75, 81, 79, 71, 90, 75, 95, 77, 94
- Highest = 95, Lowest = 71
- Range = 71 to 95 (or difference = 24)
- Limitation: Shows only extreme values; tells nothing about dispersion between extremes
(b) MEAN DEVIATION (MD)
- Average of deviations from the arithmetic mean
- Formula: M.D. = Σ(x - x̄) / n (ignoring ± sign)
Example (Park): BP of 10 individuals: 83, 75, 81, 79, 71, 95, 75, 77, 84, 90
| Diastolic BP (x) | Mean (x̄) | Deviation (x - x̄) |
|---|
| 83 | 81 | +2 |
| 75 | 81 | -6 |
| 81 | 81 | 0 |
| 79 | 81 | -2 |
| 71 | 81 | -10 |
| 95 | 81 | +14 |
| 75 | 81 | -6 |
| 77 | 81 | -4 |
| 84 | 81 | +3 |
| 90 | 81 | +9 |
| Total = 810 | | Total = 56 (ignoring ±) |
Mean = 810/10 = 81
Mean Deviation = 56/10 = 5.6
(c) STANDARD DEVIATION (SD)
- Most frequently used measure of deviation
- Defined as "Root - Mean - Square - Deviation"
- Denoted by Greek letter σ or S.D.
Formula:
S.D. = √[Σ(x - x̄)² / n] (for samples > 30)
For smaller samples: S.D. = √[Σ(x - x̄)² / (n-1)]
Properties:
- SD is always positive
- The smaller the SD, the more uniform/homogeneous the observations
- Used in calculating Standard Error, Normal Distribution, and confidence intervals
- About 68% of observations fall within ±1 SD of the mean
- About 95% of observations fall within ±2 SD of the mean
Q11. Standard Error and Standard Deviation
STANDARD DEVIATION (SD):
- Measures the variability/spread within a single sample
- Describes how individual observations vary around the sample mean
- Formula: SD = √[Σ(x - x̄)² / n]
- Used to describe the distribution of data in a sample
- A property of the sample
STANDARD ERROR (SE):
- Measures the variability of the sample mean if the study were repeated many times
- Describes how precisely the sample mean estimates the true population mean
- Formula: SE = SD / √n
- The smaller the SE, the more precise the estimate of the population mean
- Used to construct confidence intervals
- A property of the sampling distribution
Key Differences:
| Feature | Standard Deviation | Standard Error |
|---|
| What it measures | Spread of individual values around the sample mean | Precision of sample mean as estimate of population mean |
| Formula | √[Σ(x-x̄)²/n] | SD / √n |
| Decreases with larger n | No - stable | Yes - decreases |
| Used for | Describing data variability | Hypothesis testing, confidence intervals |
| Represents | Variability in the sample | Variability between samples |
Relationship:
- As sample size (n) increases, SE decreases (becomes more precise)
- SE = SD / √n - so if n increases 4 times, SE decreases by half
Confidence Interval (from Park):
- 95% CI = x̄ ± 1.96 × SE
- 99% CI = x̄ ± 2.58 × SE
"Standard deviation is a measure of variability within a sample; standard error of the mean is a measure of how accurately the sample mean estimates the population mean." - Park
All answers sourced from: Park's Textbook of Preventive and Social Medicine, pages 944-1027 (Biostatistics & Health Information chapter)