---

BIOSTATISTICS & HEALTH INFORMATION - Complete SAQ Answers

---

Q1. Define Health Information and Biostatistics

• Data that has been processed and transformed into a usable form for decision-making
• Data → Information → Intelligence (the transformation chain)
• Data = discrete observations carrying little meaning alone
• Information = data reduced, summarized, and adjusted for age/sex variations
• Intelligence = information integrated with experience and values to guide decision-makers

1. Measure health status and quantify health problems
2. Local, national, and international comparisons
3. Planning, administration, and management of health services
4. Assessing effectiveness and efficiency of health services
5. Assessing community satisfaction with health systems
6. Research into problems of health and disease

• The science of applying statistical methods to biological and medical data
• Includes collection, organization, analysis, and interpretation of data
• Deals with vital statistics - births, deaths, marriages, morbidity

1. Population-based
2. Avoid unnecessary agglomeration of data
3. Problem-oriented
4. Use functional and operational terms
5. Express information briefly and imaginatively
6. Provision for feedback of data

• Demography and vital events
• Environmental health statistics
• Health status: mortality, morbidity, disability
• Health resources: facilities, beds, manpower
• Utilization of health services
• Indices of outcome of medical care
• Financial statistics

---

Q2. Sources of Health Information ★★★★

SOURCES OF HEALTH INFORMATION
┌──────────────────────────────────────────────────┐
│  1. CENSUS (every 10 years)                      │
│  2. Registration of Vital Events (CRS/SRS)       │
│  3. Notification of Diseases                     │
│  4. Hospital Records                             │
│  5. Disease Registers                            │
│  6. Epidemiological Surveillance                 │
│  7. Morbidity Surveys                            │
│  8. Environmental Surveys                        │
│  9. Health Facility Records                      │
│ 10. Sample Surveys (NFHS, DLHS)                 │
│ 11. Vital Statistics Reports                     │
│ 12. Health Manpower Statistics                   │
│ 13. Other Routine Statistics                     │
└──────────────────────────────────────────────────┘

• Civil Registration System (CRS)
• Sample Registration System (SRS)

• Compulsorily notifiable diseases: cholera, plague, yellow fever
• Limitations: under-reporting, only tip of the iceberg

• Basic source in India where registration is defective
• Limitation: represent only those who seek care (tip of the iceberg)

• Cancer registers, TB registers
• Permanent records; more detailed than notification

• Continuous scrutiny of factors that determine disease occurrence

• National Family Health Survey (NFHS)
• District Level Household Survey (DLHS)

• Demographic: population density, movement, education
• Economic: tobacco consumption, dietary fats, per capita income
• Social security: medical insurance, sickness absence data

---

Q3. Census in India ★★★★★★★★

"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."

• Most people are usually resident in their own homes during that period

1. Demographic: Total population, age, sex distribution, sex ratio
2. Social: Literacy, education levels, marital status, religion, caste
3. Economic: Occupation, income, employment
4. Housing: Housing conditions, amenities

1. Provides base for computing vital statistical rates
2. Base line for health, demographic, and socio-economic planning
3. Population by age and sex for computing mortality/morbidity rates
4. Without census data - impossible to obtain health indicators
5. Reference for planning in medicine, human ecology, social sciences

• Full results not available quickly (takes several years to analyze)

1901 → 2011: Ten-yearly intervals
Census Act 1948 → Legal basis
Census Commissioner → Supreme officer
March 2011 → Most recent

---

Q4. Sample Registration System (SRS) ★★★

• Established by the Office of the Registrar General of India
• Introduced in 1964-65 on a pilot basis
• Provides data for states/union territories

SRS
├── Continuous enumeration by Part-time Enumerator
│   (records all births and deaths as they occur)
└── Independent retrospective survey
    (every 6 months by Supervisor)
         ↓
    Matching of two sets of data
         ↓
    Unmatched events investigated
         ↓
    Final reliable estimates

• Dual record system
• Covers rural and urban areas
• Provides state-level estimates
• Conducted continuously throughout the year

1. Crude Birth Rate (CBR)
2. Crude Death Rate (CDR)
3. Infant Mortality Rate (IMR)
4. Total Fertility Rate (TFR)
5. Age-specific fertility rates
6. Maternal Mortality Rate

• Most reliable source of vital rates in India
• Fills the gap where civil registration is incomplete
• Basis for national health policy and planning

---

Q5. Civil Registration System (CRS) ★★★

• Long tradition of registration of births and deaths
• Registration of Births and Deaths Act, 1969 (RBD Act)
• Registrar General of India is the Chief Registrar

Chief Registrar (National)
         ↓
State Chief Registrar
         ↓
District Registrar
         ↓
Sub-Registrar (taluk/block level)
         ↓
Village Registrar / Gram Panchayat

1. Live births
2. Deaths (with cause)
3. Still births / Foetal deaths
4. Marriages
5. Divorces

1. Registration is incomplete, especially in rural areas
2. Cause of death is often inaccurate
3. Under-reporting of female births and deaths
4. Deaths without medical certification
5. Births in remote areas often unregistered

---

Q6. Types of Data Presentation

DATA PRESENTATION
┌─────────────────────────────────────┐
│  A. TABULAR FORM                    │
│     - Frequency distribution table │
│                                     │
│  B. DIAGRAMS / CHARTS               │
│     1. Bar Charts                   │
│     2. Line Diagrams                │
│     3. Pie Charts                   │
│     4. Pictograms                   │
│     5. Histogram                    │
│     6. Frequency Polygon            │
│     7. Statistical Maps             │
│     8. Scatter Diagram              │
└─────────────────────────────────────┘

• Length of bar proportional to the magnitude
• Easy to prepare; enables visual comparison
• Types:
  • (a) Simple bar chart - vertical or horizontal bars
  • (b) Multiple bar chart - two or more bars grouped together
  • (c) Component bar chart - bars divided into proportional parts

• Used to show trend of events over time (e.g., malaria cases 1972-78)
• X-axis = time; Y-axis = magnitude

• Areas of segments of a circle are compared
• Each segment's area depends on angle
• Popular with laity; not preferred by statisticians
• Percentages should be indicated in segments

• Small pictures or symbols to present data
• Popular for general public
• Fractions of picture represent smaller numbers
• Essentially a form of bar chart

• Bars touching each other (no gaps)
• Used for continuous data / frequency distribution
• Area of bar proportional to frequency

• Line connecting midpoints of tops of histogram bars

• For geographic or administrative area data
• Shaded Maps: varying colours/intensities for different values
• Dot Maps: dots placed on map to show distribution

• Shows relationship between two variables
• If dots cluster around a straight line = linear relationship (correlation)

---

Q7. Sampling Methods ★★★

• A listing of all members of the universe from which sample is drawn
• Accuracy and completeness of sampling frame determines quality of sample

SAMPLING METHODS
┌──────────────────────────────────────────────────┐
│  1. SIMPLE RANDOM SAMPLING                       │
│     - Assign number to each unit                 │
│     - Use table of random numbers                │
│     - Each unit has EQUAL chance of selection    │
│     - Greatest number of possible samples        │
├──────────────────────────────────────────────────┤
│  2. SYSTEMATIC RANDOM SAMPLING                   │
│     - Pick every 5th or 10th unit               │
│     - e.g., Filaria survey: select every 10th   │
│       house after a random start                 │
│     - Fewer possible samples than #1             │
├──────────────────────────────────────────────────┤
│  3. STRATIFIED RANDOM SAMPLING                   │
│     - Population divided into strata             │
│       (age, religion, sex, etc.)                 │
│     - Sample drawn from each stratum             │
│     - Useful when strata not equally distributed │
└──────────────────────────────────────────────────┘

• Cluster Sampling: Population divided into clusters; entire clusters selected
• Multistage Sampling: Sampling done in multiple stages (state → district → village)
• Quota Sampling: Non-random; interviewer fills quota for each category
• Purposive/Judgement Sampling: Researcher selects based on judgement

• Population: Mean = μ, SD = σ (Greek letters)
• Sample: Mean = x̄, SD = s (Roman letters)

• Variation from one sample to another
• Decrease as sample size increases
• Increase as individual readings vary widely (more variability)

---

Q8. Normal Distribution Curve ★★★

        NORMAL DISTRIBUTION CURVE
              ___
           __/   \__
         _/         \_
       _/             \_
    __/                 \__
───/─────────────────────────\───
    -3σ  -2σ  -1σ   μ  +1σ +2σ +3σ

        ←─── 68.27% ───→  (±1 SD)
        ←──── 95.45% ────→  (±2 SD)
        ←───── 99.73% ─────→  (±3 SD)

1. Bell-shaped and perfectly symmetrical
2. Mean, Median, and Mode all coincide (at center)
3. Total area under the curve = 1 (or 100%)
4. Mean = 0, SD = 1 (for standard normal curve)
5. Based on infinitely large number of observations
6. Tails never touch the X-axis (asymptotic)
7. There are infinite number of normal curves (depend on mean and SD)

• Z = how many SDs a value lies from the mean
• Standardization: mean = 0, SD = 1

• Pulse of normal males = 72, SD = 2
• For pulse ≥ 80: Z = (80-72)/2 = 4
• Area for Z=4 is 0.49997
• Probability of pulse ≥ 80 = 0.5 - 0.49997 = 0.00003 (very rare)

• Defines normal biological ranges
• Basis for hypothesis testing and tests of significance
• Used to calculate confidence intervals

---

Q9. Measures of Central Tendency ★★★★

---

A. ARITHMETIC MEAN (x̄)

• Total = 810; Mean = 810/10 = 81.0 mmHg

---

B. MEDIAN

• Median = 79 mmHg (5th value out of 9)

---

C. MODE

• Mode = 75 (appears most frequently)

---

         SYMMETRIC (Normal):  Mean = Median = Mode
         
         POSITIVELY SKEWED:   Mode < Median < Mean
         
         NEGATIVELY SKEWED:   Mean < Median < Mode

---

Q10. Measures of Deviation (Dispersion) ★★★★

---

A. RANGE

• Range = 71 to 95 (or difference = 24)

---

B. MEAN DEVIATION

---

C. STANDARD DEVIATION (SD / σ)

1. Calculate the mean (x̄)
2. Find deviation of each value from mean: (x - x̄)
3. Square each deviation: (x - x̄)²
4. Add all squared deviations: Σ(x - x̄)²
5. Divide by (n-1)
6. Take square root

• Abstract number
• Gives idea of the 'spread' of the dispersion
• Larger SD = greater dispersion of values about the mean
• Used with Normal Curve: μ ± 1SD = 68.27%; μ ± 2SD = 95.45%; μ ± 3SD = 99.73%

---

Q11. Standard Error (SE) and Standard Deviation (SD)

• Measures variability within a single sample
• Shows spread of individual observations around the sample mean
• Formula: SD = √[Σ(x-x̄)²/(n-1)]
• Greek symbol: σ (population); s (sample)

• Measures variability of the sample mean itself across repeated samples
• A measure of sampling error
• Formula: SE = σ/√n (SD divided by square root of sample size)

SINGLE SAMPLE                MANY SAMPLES
                              
Individuals vary              Sample means vary
around their mean             around population mean (μ)
                              
    ↓                              ↓
STANDARD DEVIATION         STANDARD ERROR
  (SD or σ)                  (SE = σ/√n)
  
Describes spread of         Describes reliability
individual data              of the sample mean

• 95% of sample means lie within: μ ± 2 SE
• 99% of sample means lie within: μ ± 3 SE

• SE = SD/√n = 0.6/√25 = 0.6/5 = 0.12
• 95% CI = 98.14 ± 2(0.12) = 97.90 to 98.38°F

• SE of Mean = σ/√n
• SE of Proportion = √[p(1-p)/n]
• SE of Difference between means = √[(SE₁)² + (SE₂)²]

---

---

BIOSTATISTICS & HEALTH INFORMATION — SAQ Answers (8 Marks)

Park's Textbook of Preventive and Social Medicine

---

Q1. Define Health Information and Biostatistics

• Data = discrete observations carrying little meaning alone
• Information = data reduced and summarized
• Intelligence = information integrated with experience and values to guide decision-makers, policy-makers, planners

1. Measure health status and quantify health problems
2. Local, national and international comparisons
3. Planning, administration and management of health services
4. Assessing effectiveness and efficiency of health services
5. Assessing community satisfaction with health system
6. Research into problems of health and disease

1. Demography and vital events
2. Environmental health statistics
3. Health status - mortality, morbidity, disability, quality of life
4. Health resources - facilities, beds, manpower
5. Utilization of health services
6. Indices of outcome of medical care
7. Financial statistics

---

Q2. Sources of Health Information ★★★★

1. Census - every 10 years; provides demographic base data
2. Registration of vital events - births, deaths, marriages (CRS / SRS)
3. Notification of diseases - compulsory notification (cholera, plague, yellow fever); suffers from under-reporting
4. Hospital records - basic source in India; limitation: only tip of the iceberg
5. Disease registers - cancer registers, TB registers; permanent, detailed records
6. Epidemiological surveillance - continuous scrutiny of disease occurrence
7. Morbidity surveys - NFHS, DLHS, household surveys
8. Environmental surveys - water quality, air, housing
9. Health manpower statistics - doctors, nurses, beds
10. Sample surveys - 5,000-10,000 households; NFHS, DLHS
11. Vital statistics reports
12. Other routine statistics - demographic, economic, social security data
13. Non-quantifiable information - health policies, legislation, public attitudes

• Covers only a small part of total sickness
• Serious under-reporting
• Atypical/subclinical cases escape (e.g., rubella, non-paralytic polio)

---

Q3. Census in India ★★★★★★★★

• First regular census in India: 1881
• Interval: every 10 years
• Last census: March 2011
• Conducted at end of first quarter of the first year in each decade (reason: most people are at their own homes)
• Legal basis: Census Act of 1948
• Supreme officer: Census Commissioner for India

• Demographic: Total population, age, sex distribution, sex ratio
• Social: Literacy, education, marital status, religion, caste
• Economic: Occupation, income, employment
• Housing conditions: Amenities

1. Provides baseline for computing vital statistical rates
2. Base for health, demographic and socio-economic planning
3. Population by age/sex needed for mortality/morbidity rate computation
4. Without census data, impossible to obtain quantified health indicators
5. Reference for planning in medicine, human ecology, social sciences

---

Q4. Sample Registration System (SRS) ★★★

• Crude Birth Rate (CBR)
• Crude Death Rate (CDR)
• Infant Mortality Rate (IMR)
• Total Fertility Rate (TFR)
• Maternal Mortality Rate (MMR)
• Age-specific fertility rates

• Most reliable source of vital rates in India
• Fills the gap where civil registration is incomplete
• Provides state-level estimates
• Basis for national health policy

---

Q5. Civil Registration System (CRS) ★★★

1. Live births
2. Deaths (with cause of death)
3. Still births / foetal deaths
4. Marriages and divorces

1. Registration is incomplete, especially in rural areas
2. Cause of death is often inaccurate (many without medical certification)
3. Under-reporting of female births and deaths
4. Births in remote areas go unregistered

• CRS = continuous legal registration of all events (universal but incomplete in India)
• SRS = statistical sample-based survey (more reliable for vital rates)

---

Q6. Types of Data Presentation

---

1. BAR CHARTS

---

---

---

2. HISTOGRAM

---

3. FREQUENCY POLYGON

---

4. LINE DIAGRAM

---

5. PIE CHARTS

---

6. PICTOGRAMS

---

7. STATISTICAL MAPS

• Shaded Maps: Different colours/intensities for different values
• Dot Maps: Dots placed on map to show geographic distribution

8. SCATTER DIAGRAM

---

Q7. Sampling Methods ★★★

---

• Assign a number to each unit in the sampling frame
• Use a table of random numbers to determine which units are included
• Each unit has an equal chance of being drawn
• Provides the greatest number of possible samples
• Eliminates personal selection bias

---

• Pick every 5th or 10th unit at regular intervals
• Example (Park): Filaria survey in a town - 10% sample taken. Houses numbered. A random number between 1-10 selected (say 4), then every 10th house selected: 4, 14, 24, 34...
• Each unit has the same chance of selection but fewer possible samples than simple random

---

• Population deliberately divided into strata (age groups, religion, sex, etc.)
• Sample drawn from each stratum
• Useful when interested in analysing by a specific characteristic
• Particularly useful when groups not equally distributed in the population (e.g., Hindus, Christians, Muslims)

---

• Population: Mean = μ, Standard deviation = σ (Greek letters)
• Sample: Mean = x̄, Standard deviation = s (Roman letters)

---

Q8. Normal Distribution Curve ★★★

1. Bell-shaped and perfectly symmetrical
2. Mean = Median = Mode (all coincide at center)
3. Total area under curve = 1 (100%)
4. Tails never touch the X-axis (asymptotic)

• x̄ ± 1σ = 68.3% of values
• x̄ ± 2σ = 95.4% of values
• x̄ ± 3σ = 99.7% of values

• Only ONE standardized normal curve exists
• Mean = 0, Standard deviation = 1
• Mean, median and mode all coincide
• Used to estimate area under normal curve between any two ordinates

---

Q9. Measures of Central Tendency ★★★★

---

A. THE MEAN (x̄)

• Total = 810; Mean (x̄) = 810 ÷ 10 = 81.0 mmHg

• Easy to calculate and understand
• Most useful of statistical averages

• May be unduly influenced by abnormal/extreme values
• May give absurd values (e.g., average children = 4.76)

---

B. THE MEDIAN

• Not affected by extreme values
• More representative when distribution is skewed

• Requires arrangement of data
• Does not use all values in calculation

---

C. THE MODE

• Easy to understand
• Not affected by extreme items

• Exact location often uncertain
• Often not clearly defined
• Not often used in biological or medical statistics

---

Q10. Measures of Deviation (Dispersion) ★★★★

---

(a) THE RANGE

• Highest = 95, Lowest = 71
• Range = 71 to 95 (or difference = 24)

---

(b) THE MEAN DEVIATION

---

(c) THE STANDARD DEVIATION (SD)

1. Calculate mean (x̄)
2. Find deviation of each value from mean: (x - x̄)
3. Square each deviation: (x - x̄)²
4. Sum all squared deviations: Σ(x - x̄)²
5. Divide by (n-1)
6. Take square root

• It is an abstract number
• Gives idea of the 'spread' of dispersion
• Larger SD = greater dispersion of values about the mean
• Its full meaning is appreciated only in relation to the Normal Curve

---

Q11. Standard Error and Standard Deviation

---

STANDARD DEVIATION (SD)

• Measures variability of individual observations within a single sample
• Formula: SD = √[Σ(x-x̄)²/(n-1)]
• Describes spread of data around the sample mean
• Used in: data description, normal range calculation

---

STANDARD ERROR (SE)

• Distribution of means = nearly normal distribution
• Mean of sample means = population mean (μ)
• The SD of the distribution of sample means = Standard Error

• 95% of sample means lie within μ ± 2 SE
• 99% of sample means lie within μ ± 3 SE

• SE = 0.6/√25 = 0.6/5 = 0.12
• 95% Confidence limits = 98.14 ± 2(0.12) = 97.90 to 98.38°F

---

• Measures spread of individual values in a sample
• Describes variability in the data itself

• Measures reliability/precision of the sample mean
• Decreases as sample size (n) increases
• SE = SD/√n

• (a) Standard Error of the Mean = σ/√n
• (b) Standard Error of Proportion = √[p(1-p)/n]
• (c) Standard Error of Difference between two means
• (d) Standard Error of Difference between two Proportions

---

---

---

---

CHI-SQUARE TEST (χ²)

(Park's Textbook of Preventive and Social Medicine)

---

• O = Observed frequency
• E = Expected frequency
• Σ = Sum of all cells

---

---

• Proportion attacked = 36/176 = 0.204
• Proportion not attacked = 140/176 = 0.795

• Vaccine A attacked: 90 × 0.204 = 18.36
• Vaccine A not attacked: 90 × 0.795 = 71.55
• Vaccine B attacked: 86 × 0.204 = 17.54
• Vaccine B not attacked: 86 × 0.795 = 68.37

• For df = 1, the value of χ² at P = 0.05 is 3.841
• Our calculated χ² = 1.804, which is less than 3.841
• Therefore P > 0.05 → result is NOT significant
• The null hypothesis is accepted - the difference between vaccine A and vaccine B is not statistically significant and could be due to chance

---

• χ² test is used for qualitative/categorical data
• Used when comparing two or more proportions
• Result is significant when calculated χ² exceeds the table value at P = 0.05
• For a 2×2 table, df = 1 always
• df = (r-1)(c-1)

---

---

CHI-SQUARE TEST

---

---

(1) TEST THE NULL HYPOTHESIS

• Proportion attacked = 36/176 = 0.204
• Proportion not attacked = 140/176 = 0.795

• Vaccine A attacked: 90 × 0.204 = 18.36
• Vaccine A not attacked: 90 × 0.795 = 71.55
• Vaccine B attacked: 86 × 0.204 = 17.54
• Vaccine B not attacked: 86 × 0.795 = 68.37

---

(2) APPLYING THE χ² TEST

---

(3) FINDING THE DEGREE OF FREEDOM

---

(4) PROBABILITY TABLES

The test is valid only if the expected number in each cell is not less than two.

---