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Demographic Transition Theory or Demographic Cycle

The Demographic transition model (DTM) is a model used to represent the process of explaining the transformation of countries from high birth rates and high death rates to low birth rates and low death rates as part of the economic development of a country from a pre-industrial to an industrialized economy. It is based on an interpretation begun in 1929 by the American demographer Warren Thompson of prior observed changes, or transitions, in birth and death rates in industrialized societies over the past two hundred years.

Stage one ( high stationary)

• In stage one, pre-industrial society, death rates and birth rates are high and roughly in balance.
• the birth rate is constant, while the death rate fluctuates due to manmade and natural disasters as famines, floods and wars.

Stage two ( early expanding )

• In stage two, that of a developing country, the death rates drop rapidly due to improvements in food supply and sanitation, which increase life spans and reduce disease. These changes usually come about due to improvements in farming techniques, access to technology, basic healthcare, and education. Without a corresponding fall in birth rates this produces an imbalance, and the countries in this stage experience a large increase in population.

Stage three ( late expanding)

• In stage three, birth rates fall due to access to contraception, increases in wages, urbanization, a reduction in subsistence agriculture, an increase in the status and education of women, a reduction in the value of children's work, an increase in parental investment in the education of children and other social changes. Population growth begins to level off.

Stage four ( low stationary)

• During stage four there are both low birth rates and low death rates. Birth rates may drop to well below replacement level as has happened in countries like Germany, Italy, and Japan, leading to a shrinking population

• As the large group born during stage two ages, it creates an economic burden on the shrinking working population. Death rates may remain consistently low or increase slightly due to increases in lifestyle diseases due to low exercise levels and high obesity and an aging population in developed countries.

• Birth rates fluctuate, indicative of fertility control as people alter their reproduction according to socioeconomic changes.

Stage five (declining)

• The population begins to decline due to lower birth rate as compared to death rate
• Developed countries are facing this problem

England was the first country to pass through the demographic transition. This took approximately 200 years. Some other countries, such as Japan, which started the process rather later than England, completed their passage through the transition in less than half that time.

The extent to which this theory applies to less-developed societies today remains to be seen. Many countries such as China, Brazil and Thailand have passed through the DTM very quickly due to fast social and economic change. Some countries, particularly African countries, appear to be stalled in the second stage due to stagnant development and the effect of AIDS.

  1. Not applicable to less developed countries (lack of quality data, ignores HIV infection)
  2. Generalization of Europe
  3. Ignoring social change compared to economic and industrial change
  4. Unable to explain baby-boom and baby-bust syndrome
  5. Does not explain population momentum

Errors and Bias in Epidemiological Studies

Concept of Error:

In epidemiology: refers to a phenomenon in which the result or finding of the study does not reflect the truth of the fact.

Types of Error:

  1. Random (chance) Error – associated with precision
  2. Systematic Error/Bias – associated with selection 

Common Sources of Error:

  1. Selection bias
  2. Absence or inadequacy of controls
  3. Unwarranted conclusion
  4. Ignoring the periods of exposure to risk
  5. Improper interpretation of associations
  6. Mixing of non-comparable records
  7. Error of measurement

Random error/ Chance variation

  • Error that generally occurs in sampling procedure.
  • It is a divergence, due to chance alone, of an observation on a sample from the true population value, leading to lack of precision in the measurement of an association.

Picture description:

Out of a sample of 100 people, 3 consecutive sample drawn randomly may contain:

  • 0% diseased people
  • 10% diseased people
  • 70% diseased people

This is called random error where the error is due to chance.
The only way to reduce it is to increase the size of sample.
Elimination of error is not possible

Sources of random error:

  1. Individual biological variation
  2. Sampling error
  3. Measurement error

Types of Random Errors

  1. Type I Error – alpha error
  2. Type II Error – beta error

How to reduce Random Error?
Increase the size of the study.

Systemic Error/Bias

Any process or attempts in any stage of the study from designing to its execution to the application of information from the study which produces results or conclusions that differ systematically from truth.

A. Selection Bias

  • A distortion in true study finding due to improper selection procedures or it is due to an effect of selection process
  • Most common type of bias.

Some potential sources of selection biases:

  1. Self selection bias
  2. Selection of control group
  3. Selection of sampling frame
  4. Loss to follow up
  5. Improper diagnostic criteria
  6. More intensive interview to desired subjects etc.

B. Information Bias

It is distortion in true study finding due to improper information/lack of information or misclassification.

Potential sources of Information Bias:

  1. Invalid instrument
  2. Incorrect diagnostic criteria
  3. Misclassifications
  4. Recall laps error
  5. Interviewing techniques
  6. Losses to follow up, attrition/experimental mortality, etc.

C. Confounding Bias

  • Special type of Bias
  • The term “confounding” – effect of extraneous variable that entirely or partially explains the apparent association between the study exposure and the disease.
  • It is a bias that results when a study factor effect is mixed, in the data, with effects of extraneous variable or the third variables.

Confounding Variables
A variable is a confounder if:

  1. It is an independent risk factor (cause) of disease.
  2. It is unevenly distributed among the exposed and the non-exposed
  3. It is not on the causal pathway between exposure and the disease.

Methods of Controlling Confounding in Epidemiological Study

In two stages:

In designing stage

In analysis stage
Statistical modeling (multivariate)

Principles Of Health Education

Purpose/Aims of Health Education:
  • To ensure that health is an assets in the community.
  • To equip the people with skills, knowledge and attitude.
  • To promote the development and proper use of health service.
Principles of Health Education

It is a psychological principle that people are unlikely to listen to those things which are not to their interest.

It should aim at encouraging people to work actively with health workers and others identifying their own health problems and also in developing solution and plans to work them out.

Known to unknown
Start where the people are and with what they understand and then proceed to new knowledge

In Health Education, we must know the level of understanding, education and literacy of people to whom the teaching is directed.

Repetition at interval is extremely useful for understanding all the news.

Every individual has a fundamental desire to learn. Stimulation or awakening of desire of learning called motivation.

Health educators must be aware of the various barriers of communication and cultural background of the community.

Learning by doing
The Chinese proverb “if I hear, I forget. If I see, I remember. If I do, I know” illustrate the importance of learning by doing.

Good Human Relationship

Biostatisitcs Exercise

1.Suppose it is known that in a certain population 10 percent of the population is colour blind. If a random sample of 25 people is drawn from this population, find the probability that
a) five or fewer will be colour blind
b) six or more will be colour blind
c) between six and nine will be colour blind
d) two, three or four will be colour blind

2.Suppose that 24 percent of a certain population have blood group A. for a sample of 25 people drawn from this population, find the probability that
a) Exactly three will have group A
b) Three  or more will have group A
c) Fewer than three will have group A
d) Exactly five will have group A

3. A hospital administrator, who has been studying daily emergency admissions over a period of several years, has concluded that they are distributed according to the poisson law. Hospital records reveal that emergency admissions have averaged three per day during this period. Find the probability that
a. exactly two emergency admissions will occur on a given day.
b. no emergency admission will occur on a given day.
c. either three or four emergency cases will be admitted on a given day.

4. If the mean number of serious accidents per year in a large factory (where the number of employees remain constant ) is five, find the probability that in the current year there will be
a. exactly seven accidents.
b. ten or more accidents.
c. No accidents.
d. Fewer than five accidents.

5. If the total cholesterol value for a certain population is approximately normally distributed with a mean of 200mg/100ml. And a standard deviation of 20mg/100ml. Find the probability that an individual picked at random from this population will have a cholesterol value
a. Between 180 and 200mg/100ml.
b. Greater than 225mg/100ml.
c. Less than 150mg/100ml.
d. Between 190 and 210mg/100ml

6. Average wt of baby at birth is 3.05 kg with the sd of 0.39 kg. if the birth wts follow normal distribution will you take
a. wt of 3.9 kg as abnormal?
b. wt of 2.5 kg as normal?

7. Menstrual cycle in women following normal distribution has mean of 28 days and sd of 2 days. How frequently would you expect a menstrual cycle of
a. more than 30 days?
b. less than 20 days?

8. A researcher was interested to determine if  urine levels of a certain chemical in pre-term infants with late metabolic acidosis and pre-term infants without the condition differs. The mean, s. d. and sample sizes are as follows:

With condition
Without condition

9. A health researcher wants to estimate the mean hb level in the community. Preliminary information is that this mean is about 150 mg/l with sd of 32 mg/l. if a difference of up to 5 mg/l in either side in the estimate can be tolerated, how many subjects should be included in the study?

10. An intervention programme for tobacco users is to be implemented in certain community. Find the required sample size when the proportion of tobacco user in the community is reported to be 20% by some other study and a difference of upto 3 in either side is tolerable.

11. In a length of hospitalization study conducted by several cooperating hospitals, a random sample of 64 peptic ulcer patients was drawn from a list of all peptic ulcer patients ever admitted to the participating hospitals and the length of  hospitalization per admission was determined for each. The mean length of stay was found to be 8.25 days. If the population s. d. is known to be 3 days, can it be concluded that the mean hospital stay is more than 7 days, less than 9 days and different than 7 days.

In the above problem, if population SD is not known and sample SD is 3 days and sample size is 25 records of patients, solve for all three conditions.

12. Protoporphyrin levels were measured in two samples of subjects. Sample 1 consisted of 50 adult male alcoholics with ringed sideroblasts in the bone marrow. Sample 2 consisted of 40 apparently healthy non alcoholic males.
Can we conclude that protopophyrin levels are higher in alcoholic population than in non alcoholic?
The mean and SD were
Sample number

In the above problem if SDs are sample SDs and sample sizes are 22 for both samples apply t test for unequal variances and equal variances

13. Researchers wish to know if the data they have collected provide sufficient evidence to indicate a difference in mean serum uric acid levels between normal individuals and individuals with mongolism at 5% level. The data are as follows:

4.5 mg/100ml
Normal individuals
3.4 mg/100ml
a)            Let the populatiom s. d. for both is 1, solve using z test.

b)            Let the sample s. d. for both is 1,  assume equality of variances and solve. Assume unequal variances and solve.

14. Can we conclude that chronically ill children tend on average, to be less self confident than healthy children? A test designed to measure self confidence was administered to 32 chronically ill and 32 healthy children. The mean scores and s. d. were as follows.

Ill group
Well group

15. A group of 350 adults who participated in a health survey were asked whether or not they were on diet. The responses by sex are as follows:


On diet
Not on diet

Do these data suggest that being on diet is dependent on sex? Let a =. 05

16. A sample of 500 college students participated in a study designed to evaluate the level of college students’ knowledge of a certain group of common diseases. The following table shows the students classified by major field of study and level of knowledge of group of diseases.

Knowledge of disease

Major field

17. A study of 190 pregnancies yielded the following results on the relationship between hypertension of mother and a certain complication of pregnancy.
                                                                     Mother hypertensive
A certain complication of pregnancy
Do these data suggest that the two conditions are not independent?

18. Determine if there is association between scabies amongst the school children and the socio economic status.

Socio economic status
Scabies status
With scabies
Without scabies

Approaches to address maternal health problems in Nepal

Maternal mortality is one of the key indicators of the status of reproductive health care service delivery and utilization, and also it also can be an indicator of women’s status in a society. The maternal mortality rate in Nepal is 539 per 100,000 live births, which is one of the highest in the world (According to Kathmandu University Medical Journal ,2006).

The reasons for such high rate of Maternal mortality in Nepal are:
  1. Under utilization of the maternal health services (Poor accessibility, limited infrastructures and manpower)
  2. Political instability (Lack of security, conflicts, strikes)
  3. Limited health infrastructure (Especially in rural areas)
  4. Lack of resources and shortage of trained health professional
  5. Women’s position in society and women’s vulnerability (Low status of women in male dominated society)
  6. Affordability (37.7% below poverty line)
  7. Communication and transportation (In rural areas, to reach hospitals and health centers, people have to walk for hours)
Status of some programs and policies on maternal health:

Nepal’s Safe Motherhood Programme is coordinated by the Family Health Division of the Directorate of Health Services of MOH, within the context of the National Reproductive Health Programme. Under this programme a Safe Motherhood Committee has been established, in which most stakeholders participate and contribute, amongst others, to policy and strategy development.

Modern Birth centers are being established in rural areas by UNICEF

Health care delivery remains largely the responsibility of the Ministry of Health, although the non-governmental organisations (NGO’s) are increasingly providing health services, particularly in the urban areas of the country.

Safe motherhood Policy (1998) emphasized on:
  1. increasing the accessibility, availability and utilization of maternal health care
  2. strengthening technical capacity of service providers at all levels
  3. strengthening referral services for maternity care, particularly at the district level
  4. specific emphasis on appropriate referral
  5. increasing the availability and use of contraceptives
  6. raising public awareness about the importance of the health care of women and in particular maternal care
  7. improving the legal and social status of women
Activities carried out for the improvement of maternal health:
  1. Establishment of Safe Motherhood Sub-committee
  2. Establishment of Reproductive Health Steering Committee
  3. Establishment of Reproductive Health Coordinating Committee
  4. Formulation of National Reproductive Health Strategy (1998)
  5. Development of reproductive health (including maternal, and neonatal) clinical protocol for paramedics, nurses and medical officers
  6. Formulation of long term Safe Motherhood Plan (2002-2017)
  7. Development of Health Sector Strategy: An Agenda for Reform
  8. Development of Health Sector Program: Implementation Plan, 2004-2009
  9. Development of National Neonatal Strategy (2004)
  10. National Policy on Safe Abortion Care
Approaches for improving maternal health:

1) Improving health service utilization
  • Contact with health care providers during pregnancy, identification of pregnancy complications and timely referral to an appropriate institution is essential to prevent maternal death.
  • Antenatal care (ANC) is an opportunity to inform women about the danger signs and symptoms for which help should be sought from health care provider.
2) Providing education and knowledge
  • Best strategy to improve maternal health
  • Educated women are more likely to realize the benefits of using maternal health services.
3) Involving men in maternal health matters
  • Since men are the primary decision maker of most Nepalese families, men’s involvement in maternal health matter could promote a better relationship between men and women in household in women empowerment
4) Making services affordable
  • Making services affordable for all poor people is essential to improve the maternal health.
  • National policies development that ensure removal of financial barriers like fees for essential services and supplies should be implemented, so that women can easily have an access to skilled care.
5) More Budget Allocation in Health Sector

6) Improving communication and transportation system
  • Improved transportation system can save women life when they need emergency obstetric services.
7) Expanding contraceptive options
  • Increase and Ensure the availability of a wide range of family planning supplies
  • Provide training, staffing, and supervisory support at clinics and hospitals
  • Use mobile family planning clinics to reach clients in underserved areas