This document provides demographic indicators and data about Thailand's population in 2016. It defines key demographic indicators such as sex ratio, median age, and age-dependent ratio. It then presents Thailand's values for these indicators in 2016, showing a sex ratio of 0.94 males to females, a median age of 35.46 years, and an age-dependent ratio of 52.27. The document also discusses fertility indicators and uses data from 2009 to calculate Thailand's crude birth rate, general fertility rate, total fertility rate, and other metrics.
This document discusses various measures of fertility used in statistical demography. It provides census data from Andhra Pradesh, India from 2001 and 2011 to calculate and compare measures like crude birth rate, gross fertility rate, age-specific fertility rate, total fertility rate, and gross reproductive rate. The key measures saw declines from 2001 to 2011, indicating falling fertility rates in Andhra Pradesh over that time period. Graphs are provided to visually compare the measures between the two time periods. Studying changes in fertility rates over time allows for improved population and resource planning.
Introduction to rural sociology 101 Lecture 6 population growth and character...Marina Hanna
The document provides demographic information about Egypt's population including estimates, growth rates, and population structure. Some key points:
- Egypt's population in January 2017 was estimated at 92.1 million using natural increase method (births minus deaths).
- The population is distributed unevenly across governorates with Cairo and Alexandria having the largest populations at 10.4% and 5.4% respectively.
- Egypt's population is estimated to be 57.3% rural and 42.7% urban as of 2016.
- A population pyramid shows Egypt has a youthful population structure with over 35% under age 15.
- The crude birth rate, death rate, and other demographic indicators are included to
- The document provides demographic data on the population and age groups of Nigeria and several Nigerian states.
- The data shows that the vast majority (over 80% in most cases) of the population is under 50 years old in all areas surveyed.
- The largest percentages are in younger age groups, with over 15% typically in the 0-4 and 5-9 age ranges.
- This demonstrates that Nigeria and its states have exceptionally young populations, with most people not yet reaching middle age.
Rachel Franklin, a professor of geographical analysis, discusses the implications of demographic change for rural policies. She notes that population aging is a global trend, as seen in data showing South Korea's declining birth rates and aging population structure. Franklin emphasizes the importance of inclusive, age-friendly rural policies that consider well-being across all age groups. She argues for planning rural development with current and future residents in mind, using intergenerational approaches and technologies. Good policy, Franklin states, requires access to reliable local data on demographic and other trends.
This document discusses various methods to evaluate the accuracy of age data, including errors in reported ages. It describes Whipple's Index, Myer's Index, Age Ratios, Age Ratio Scores, Age Specific Sex Ratios, Sex Ratio Scores, and the UN Joint Score. These indices are calculated using population data to identify issues like digit preference, under-enumeration of certain age groups, and inconsistencies in age and sex ratios that indicate errors in the age data. Graphs and examples from India's 2011 census are provided to illustrate the application and interpretation of these evaluation methods.
Standardization of rates by Dr. Basil TumainiBasil Tumaini
Standardization of rates by Dr. Basil Tumaini, presented during the residency at Muhimbili University of Health and Allied Sciences, Epidemiology class
The document discusses aging population trends in Malaysia and employment patterns among older workers. It notes that Malaysia is expected to become an aged society by 2018. While the working age population is projected to increase, the young and old dependent populations will decline and rise respectively. The literature review found that age remains a barrier to training access and job loss has long-term employment impacts for older workers. The study aims to profile older employment and identify factors influencing workforce participation among those aged 60 and above.
This document discusses various measures of fertility used in statistical demography. It provides census data from Andhra Pradesh, India from 2001 and 2011 to calculate and compare measures like crude birth rate, gross fertility rate, age-specific fertility rate, total fertility rate, and gross reproductive rate. The key measures saw declines from 2001 to 2011, indicating falling fertility rates in Andhra Pradesh over that time period. Graphs are provided to visually compare the measures between the two time periods. Studying changes in fertility rates over time allows for improved population and resource planning.
Introduction to rural sociology 101 Lecture 6 population growth and character...Marina Hanna
The document provides demographic information about Egypt's population including estimates, growth rates, and population structure. Some key points:
- Egypt's population in January 2017 was estimated at 92.1 million using natural increase method (births minus deaths).
- The population is distributed unevenly across governorates with Cairo and Alexandria having the largest populations at 10.4% and 5.4% respectively.
- Egypt's population is estimated to be 57.3% rural and 42.7% urban as of 2016.
- A population pyramid shows Egypt has a youthful population structure with over 35% under age 15.
- The crude birth rate, death rate, and other demographic indicators are included to
- The document provides demographic data on the population and age groups of Nigeria and several Nigerian states.
- The data shows that the vast majority (over 80% in most cases) of the population is under 50 years old in all areas surveyed.
- The largest percentages are in younger age groups, with over 15% typically in the 0-4 and 5-9 age ranges.
- This demonstrates that Nigeria and its states have exceptionally young populations, with most people not yet reaching middle age.
Rachel Franklin, a professor of geographical analysis, discusses the implications of demographic change for rural policies. She notes that population aging is a global trend, as seen in data showing South Korea's declining birth rates and aging population structure. Franklin emphasizes the importance of inclusive, age-friendly rural policies that consider well-being across all age groups. She argues for planning rural development with current and future residents in mind, using intergenerational approaches and technologies. Good policy, Franklin states, requires access to reliable local data on demographic and other trends.
This document discusses various methods to evaluate the accuracy of age data, including errors in reported ages. It describes Whipple's Index, Myer's Index, Age Ratios, Age Ratio Scores, Age Specific Sex Ratios, Sex Ratio Scores, and the UN Joint Score. These indices are calculated using population data to identify issues like digit preference, under-enumeration of certain age groups, and inconsistencies in age and sex ratios that indicate errors in the age data. Graphs and examples from India's 2011 census are provided to illustrate the application and interpretation of these evaluation methods.
Standardization of rates by Dr. Basil TumainiBasil Tumaini
Standardization of rates by Dr. Basil Tumaini, presented during the residency at Muhimbili University of Health and Allied Sciences, Epidemiology class
The document discusses aging population trends in Malaysia and employment patterns among older workers. It notes that Malaysia is expected to become an aged society by 2018. While the working age population is projected to increase, the young and old dependent populations will decline and rise respectively. The literature review found that age remains a barrier to training access and job loss has long-term employment impacts for older workers. The study aims to profile older employment and identify factors influencing workforce participation among those aged 60 and above.
The document discusses the economic challenges of an aging population in Hong Kong. It notes that Hong Kong's population is aging rapidly due to decreased birth rates and increased life expectancy. This aging population will place significant burdens on social welfare and medical systems as expenditures increase. It will also slow economic growth by decreasing the proportion of working individuals and reducing tax revenue from salaries. Solutions to address these challenges are debated.
The following slides provide the background data and information that have informed the future trends identified under the population theme. This presentation should be viewed alongside those for the other themes in order for the wider picture to be understood.
Martin Tod - Men’s Health Forum - Being a middle-aged man can be fatal! - IQ ...IQ_UK
An overview of the issues affecting men’s health and how they impact sickness levels in the UK. Includes guidance on how employers can provide effective support to their employees.
A visão geral da demografia da África do Sul é o tema da apresentação exibida pelo Departamento de Desenvolvimento Social da República da África do Sul, no dia 20 de fevereiro, durante a reunião plenária que marcou o início das discussões do seminário “População e Desenvolvimento na Agenda do Cairo: balanço e desafios”. Detalhes em: www.sae.gov.br
This document discusses health issues that disproportionately affect men in the UK. It provides statistics showing that men have higher rates of death under age 75 than women, and shorter life expectancies. Certain diseases like circulatory disease and cancer have higher mortality rates among men. Men also have higher rates of obesity, smoking, alcohol-related hospital admissions, and long-term health conditions than women. However, men are less likely than women to recognize symptoms of health conditions and use NHS services. Addressing these health issues could help reduce avoidable male deaths.
Esta apresentação traz o perfil social e demográfico da África do Sul, levantado a partir de dados coletados pelo Statistics AS, Instituto Nacional de estatística da África do Sul. Ela foi divulgada durante o seminário “População e Desenvolvimento na Agenda do Cairo: balanço e desafios”, realizado nos dias 21 e 22 de fevereiro, em Brasília. Para mais informações, acesse: www.sae.gov.br
Presentation made by Martin Tod, Chief Executive of the Men's Health Forum, to the Cross-Party Parliamentary Group on Health Inequalities on January 21, 2020
In a recent national South African health survey measuring the health of the nation, it was found that 74% of South Africans think their fellow citizens are overweight, while only 34% of people considered themselves as overweight or obese. The national survey, which was released in Johannesburg this week, was commissioned by GlaxoSmithKline (GSK) and conducted by independent marketing insight consultancy, Added Value.
The document provides population and economic statistics for an administrative region from 2009 to 2015. Some key points:
- The total population declined slightly from over 1 million in 2009 to just under 1 million in 2015, with the urban population remaining around 356,000-357,000.
- The number of employed increased from around 322,000 to over 366,000 while unemployment fell from 5.3% to 4.5%.
- The number of enterprises grew from 5,492 to over 6,300, with the majority being small and micro-sized. The industrial, wholesale, and transportation sectors employed the most people.
- Agricultural land was predominantly used for cereals and forage. Milk and dairy
Presentation to gm live conference 15 may 2014Mark Beatson
This document discusses several long-term trends that are shaping the global workforce: de-industrialization and the rise of knowledge-based services; advancing technology and globalization; an aging population; more women in the labor market; increased educational attainment; and changing employment relationships. It provides statistics and analysis on each trend, showing how forces like longer life expectancy, reduced fertility rates, and greater access to education are altering the makeup of the global workforce. The document aims to stimulate debate about how these trends will influence the future of work.
This document discusses HIV/AIDS trends and data in Georgia. It provides HIV incidence rates from 2005 to 2019 that have been generally increasing over time. The main routes of HIV transmission are reported to be heterosexual contact (48%), injection drug use (37%), and homosexual contact (11%). HIV prevalence is highest in the Abkhazia region and among people aged 25-34. Preventive measures are needed to control the disease given its rising incidence rates.
During 2014, ILC-UK, supported by specialist insurance company, Partnership Assurance Group plc (Partnership), is undertaking a series of events to explore the relationship between our changing demography and public policy.
The second event in the series will explore how much we really know about life expectancy at the highest ages. How many of us are living to 90 and beyond? Why have estimates of life expectancy required revision? What does this tell us about increasing longevity? And what does this trend mean for public policy and long-term population planning?
South Africa’s mid-year population is estimated to have increased to 57,73 million in 2018, representing an overall increase of 1,55% between 2017 and 2018. Gauteng continues to record the largest share of the population with approximately 14,7 million people (25,4%) living in the province. The second largest population with 11,4 million people (19,7%) remain s KwaZulu-Natal and Northern Cape remains the province with the smallest share of the South African population at approximately 1,23 million (2,1%). The Mid-year population estimates 2018 report released by Statistics South Africa, further indicate that the female population in the country has remained stable year on year at approximately 51% (approximately 29,5 million).
Read more here: http://www.statssa.gov.za/?page_id=1854&PPN=P0302
1 009 065 births were registered in 2018. This includes the total number of births that occurred and were registered for the year 2018, which was 927 113, as well as 81 952 late registrations. This means that 8,1% of births registered during 2018 were registered late. According to the Births and Deaths Registration Amendment Act, a birth must be registered within 30 days of occurrence. However, not all births are registered on time. The report shows that late registration of births, after the lapse of 30 days but before a year, declined from 26,7% in 2014 to 14,2% in 2018. Overall, in the 5-year period (2014–2018), there has been a significant improvement in terms of birth registrations within 30 days from 60,1% in 2014 to 79,6% in 2018.
Read more here: http://www.statssa.gov.za/?p=12586
Age structure, twitter, joint family systemIrfan Hussain
This document discusses three indicators: age structure, Twitter, and the joint family system. It provides demographic data on India's population structure broken down by age and sex. It defines Twitter as an online social media and microblogging service that allows users to post short text updates. The document outlines the history of Twitter and how it is used for business, media, and development. It defines the joint family system as multiple generations living together and providing mutual support, and discusses how this system can affect home ownership in Pakistan.
LMIC Senior Economist Behnoush Amery presented on post-secondary education and gender earning differentials at the Canadian Research Data Centre Network’s National Conference in Halifax, Nova Scotia.
The document discusses trends in Australia's aging population from 1901 to 2061. Some key points are:
- The percentage of the population aged 65 and over is projected to increase from 14% in 2013 to 31% in 2061.
- Labor force participation rates of those aged 55 and over have been increasing steadily since the late 1970s.
- An aging population can provide economic and social benefits such as a decreased percentage of life spent childrearing, more opportunity for work and volunteering, and potentially less crime and violence.
HealthCare System in Thailand:Past -
Present and Where is the Future ?
Dr. Pradit Sintavanarong
Minister of Ministry of Public Health, Thailand
ริชมอนด์ 11-10-56
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
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The document discusses the economic challenges of an aging population in Hong Kong. It notes that Hong Kong's population is aging rapidly due to decreased birth rates and increased life expectancy. This aging population will place significant burdens on social welfare and medical systems as expenditures increase. It will also slow economic growth by decreasing the proportion of working individuals and reducing tax revenue from salaries. Solutions to address these challenges are debated.
The following slides provide the background data and information that have informed the future trends identified under the population theme. This presentation should be viewed alongside those for the other themes in order for the wider picture to be understood.
Martin Tod - Men’s Health Forum - Being a middle-aged man can be fatal! - IQ ...IQ_UK
An overview of the issues affecting men’s health and how they impact sickness levels in the UK. Includes guidance on how employers can provide effective support to their employees.
A visão geral da demografia da África do Sul é o tema da apresentação exibida pelo Departamento de Desenvolvimento Social da República da África do Sul, no dia 20 de fevereiro, durante a reunião plenária que marcou o início das discussões do seminário “População e Desenvolvimento na Agenda do Cairo: balanço e desafios”. Detalhes em: www.sae.gov.br
This document discusses health issues that disproportionately affect men in the UK. It provides statistics showing that men have higher rates of death under age 75 than women, and shorter life expectancies. Certain diseases like circulatory disease and cancer have higher mortality rates among men. Men also have higher rates of obesity, smoking, alcohol-related hospital admissions, and long-term health conditions than women. However, men are less likely than women to recognize symptoms of health conditions and use NHS services. Addressing these health issues could help reduce avoidable male deaths.
Esta apresentação traz o perfil social e demográfico da África do Sul, levantado a partir de dados coletados pelo Statistics AS, Instituto Nacional de estatística da África do Sul. Ela foi divulgada durante o seminário “População e Desenvolvimento na Agenda do Cairo: balanço e desafios”, realizado nos dias 21 e 22 de fevereiro, em Brasília. Para mais informações, acesse: www.sae.gov.br
Presentation made by Martin Tod, Chief Executive of the Men's Health Forum, to the Cross-Party Parliamentary Group on Health Inequalities on January 21, 2020
In a recent national South African health survey measuring the health of the nation, it was found that 74% of South Africans think their fellow citizens are overweight, while only 34% of people considered themselves as overweight or obese. The national survey, which was released in Johannesburg this week, was commissioned by GlaxoSmithKline (GSK) and conducted by independent marketing insight consultancy, Added Value.
The document provides population and economic statistics for an administrative region from 2009 to 2015. Some key points:
- The total population declined slightly from over 1 million in 2009 to just under 1 million in 2015, with the urban population remaining around 356,000-357,000.
- The number of employed increased from around 322,000 to over 366,000 while unemployment fell from 5.3% to 4.5%.
- The number of enterprises grew from 5,492 to over 6,300, with the majority being small and micro-sized. The industrial, wholesale, and transportation sectors employed the most people.
- Agricultural land was predominantly used for cereals and forage. Milk and dairy
Presentation to gm live conference 15 may 2014Mark Beatson
This document discusses several long-term trends that are shaping the global workforce: de-industrialization and the rise of knowledge-based services; advancing technology and globalization; an aging population; more women in the labor market; increased educational attainment; and changing employment relationships. It provides statistics and analysis on each trend, showing how forces like longer life expectancy, reduced fertility rates, and greater access to education are altering the makeup of the global workforce. The document aims to stimulate debate about how these trends will influence the future of work.
This document discusses HIV/AIDS trends and data in Georgia. It provides HIV incidence rates from 2005 to 2019 that have been generally increasing over time. The main routes of HIV transmission are reported to be heterosexual contact (48%), injection drug use (37%), and homosexual contact (11%). HIV prevalence is highest in the Abkhazia region and among people aged 25-34. Preventive measures are needed to control the disease given its rising incidence rates.
During 2014, ILC-UK, supported by specialist insurance company, Partnership Assurance Group plc (Partnership), is undertaking a series of events to explore the relationship between our changing demography and public policy.
The second event in the series will explore how much we really know about life expectancy at the highest ages. How many of us are living to 90 and beyond? Why have estimates of life expectancy required revision? What does this tell us about increasing longevity? And what does this trend mean for public policy and long-term population planning?
South Africa’s mid-year population is estimated to have increased to 57,73 million in 2018, representing an overall increase of 1,55% between 2017 and 2018. Gauteng continues to record the largest share of the population with approximately 14,7 million people (25,4%) living in the province. The second largest population with 11,4 million people (19,7%) remain s KwaZulu-Natal and Northern Cape remains the province with the smallest share of the South African population at approximately 1,23 million (2,1%). The Mid-year population estimates 2018 report released by Statistics South Africa, further indicate that the female population in the country has remained stable year on year at approximately 51% (approximately 29,5 million).
Read more here: http://www.statssa.gov.za/?page_id=1854&PPN=P0302
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Read more here: http://www.statssa.gov.za/?p=12586
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- An aging population can provide economic and social benefits such as a decreased percentage of life spent childrearing, more opportunity for work and volunteering, and potentially less crime and violence.
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LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
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significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
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to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
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Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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1. Truc Ngoc Hoang Dang, Ph.D.
21 January 2022
PRPR 101
Population and Development
BASIC DEMOGRAPHIC INDICATORS
2. 2
Outline
• Definition of demographic indicators
• Type of demographic indicators
• Lecture
• Quiz
60 minutes
45 minutes
3. 3
Indicator
“something that shows what a situation is like”
(Cambridge English Dictionary)
“a measurement or value which gives you
an idea of what something is like”
(Collin English Dictionary)
4. 4
• Size
• Age and sex structure
• Distribution
• Fertility
• Mortality
• Migration
Demographic composition
6. 6
Age and sex indicators
1. Sex ratio
2. Median age
3. Age-dependent ratio
7. 1. Sex ratio
• Proportion of males to females in a population
7
8. Thai population by age group and sex in 2016
Age groups Male Female Total
0 785,000 752,000 1,537,000
1-4 1,104,000 1,054,000 2,158,000
5-9 1,944,000 1,855,000 3,799,000
10-14 2,116,000 2,030,000 4,146,000
15-19 2,272,000 2,202,000 4,474,000
20-24 2,310,000 2,276,000 4,586,000
25-29 2,175,000 2,177,000 4,352,000
30-34 2,202,000 2,257,000 4,459,000
35-39 2,427,000 2,555,000 4,982,000
40-44 2,501,000 2,679,000 5,180,000
45-49 2,589,000 2,821,000 5,410,000
50-54 2,416,000 2,668,000 5,084,000
55-59 2,060,000 2,308,000 4,368,000
60-64 1,672,000 1,907,000 3,579,000
65 + 3,150,000 4,053,000 7,203,000
T
otal 31,723,000 33,594,000 65,317,000
Sex ratio at birth
= 1.05 m for every f
8
Sex ratio of Thai pop
= 0.94 m for every f
103<Sex ratio at birth <107
9. 2. Median age
• Median = the "middle" value in the list of numbers
• Median age = the point at which half the population is older than
that age and half is younger
Example:
• 40 people < 30 years-old
• 40 people > 30 years-old
30 years-old is median age
10. 15
Formula
Md= Imd +[N/2 - ∑ fx)/ fmd]* i
Imd = age at start of the age group that half population is.
N = total number of population
∑ fx = sum of population before the level of age group that half of
population is
fmd = population at age group that half of population is
i = range of age group
11. Age groups Male Female T
otal
< 5 1,889,000 1,806,000 3,695,000
5-9 1,944,000 1,855,000 3,799,000
10-14 2,116,000 2,030,000 4,146,000
15-19 2,272,000 2,202,000 4,474,000
20-24 2,310,000 2,276,000 4,586,000
25-29 2,175,000 2,177,000 4,352,000
30-34 2,202,000 2,257,000 4,459,000
35-39 2,427,000 2,555,000 4,982,000
40-44 2,501,000 2,679,000 5,180,000
45-49 2,589,000 2,821,000 5,410,000
50-54 2,416,000 2,668,000 5,084,000
55-59 2,060,000 2,308,000 4,368,000
60-64 1,672,000 1,907,000 3,579,000
65 + 3,150,000 4,053,000 7,203,000
Total 31,723,000 33,594,000 65,317,000
Thai population 2016 (NESDB 2013)
N = total number
of population16
Imd = age at start
of the age group
that half
population is
= 35 years
i = range of
age group
= 5
∑ f = sum of
x
population before
the level of age
group that half of
population is.
= 29,511,000
md
f = population
at age group that
half of population
is.
= 34,493,000
Md= Imd +[N/2 - ∑ fx)/ fmd]* i
1
2
3
4
5
12. Median age of Thai population 2016
Md= Imd +[N/2 - ∑ fx)/ fmd]* i
Md = 35 + [(65,317,000/2) – 29,511,000)/34,493,000]*5
= 35.456
Imd = age at start of the age group that half population is.
N = total number of population.
∑ fx = sum of population before the level of age group that half of population is.
fmd = population at age group that half of population is.
i = range of age group
13. Age groups Male Female T
otal
< 5 1,889,000 1,806,000 3,695,000
5-9 1,944,000 1,855,000 3,799,000
10-14 2,116,000 2,030,000 4,146,000
15-19 2,272,000 2,202,000 4,474,000
55-59 2,060,000 2,308,000 4,368,000
60-64 1,672,000 1,907,000 3,579,000
65 + 3,150,000 4,053,000 7,203,000
Total 31,723,000 33,594,000 65,317,000
20-24 2,310,000 2,276,000 4,586,000
25-29 2,175,000 2,177,000 4,352,000
30-34 2,202,000 2,257,000 4,459,000
35-39 2,427,000 2,555,000 4,982,000
40-44 2,501,000 2,679,000 5,180,000
45-49 2,589,000 2,821,000 5,410,000
50-54 2,416,000 2,668,000 5,084,000
<20 = young population
20-29 = middle-age population
30+ = older population
In 2016, the median age in Thailand was 35,
signifying an older population.
18
Thai population 2016 (NESDB 2013)
14. Median age of Singaporeans
https://www.singstat.gov.sg/modules/infographics/population 19
15. 20
3. Age-dependent ratio
• The ratio of persons in the “dependent” ages
• In Thailand:
– dependent ages = age under 15 & over 60
– economically productive ages = 15-59 years
16. Age groups Male Female T
otal
< 5 1,889,000 1,806,000 3,695,000
5-9 1,944,000 1,855,000 3,799,000
10-14 2,116,000 2,030,000 4,146,000
15-19 2,272,000 2,202,000 4,474,000
20-24 2,310,000 2,276,000 4,586,000
25-29 2,175,000 2,177,000 4,352,000
30-34 2,202,000 2,257,000 4,459,000
35-39 2,427,000 2,555,000 4,982,000
40-44 2,501,000 2,679,000 5,180,000
45-49 2,589,000 2,821,000 5,410,000
50-54 2,416,000 2,668,000 5,084,000
55-59 2,060,000 2,308,000 4,368,000
60-64 1,672,000 1,907,000 3,579,000
65 + 3,150,000 4,053,000 7,203,000
Thai population 2016 (NESDB 2013)
Population under
15 years old
= 11,640,000
1
2
3
((Pop under age 15 + Pop over age 60)
/(Pop age 15-59))*k
Population over
60 years old
= 10,782,000
Population age
15-59 years old or
working age
population
= 42,895,000
17. Formula
((Pop under age 15 + Pop over age 60) /(Pop age 15-59))*k
= ((11,640,000+10,782,000) / 42,895,000)*100
= 52.272
*For every 100 people in the working ages there are 52 people in
the dependent ages
The “constant ” - an assigned
value of
100, 1,000, 10,000 or 100,000,
which
represents a standard population.
21
18. 22
Formula
((Pop under age 15 + Pop over age 60) /(Pop age 15-59))*k
Child dependent ratio =?
Elderly dependent ratio =?
19. 23
Formula
((Pop under age 15 + Pop over age 60) /(Pop age 15-59))*k
Child dependent ratio = (Pop under age 15/Pop age 15-59)*k
Elderly dependent ratio = (Pop over age 60/Pop age 15-59)*k
20. 24
Sex ratio, median age & age-dependent ratio of Thai population in
2014 and 2016
Indicators 2014 2016
Sex ratio 94.63 94.43
Median age 35.34 35.46
Age-dependent ratio 50.90 52.27
• Child dependent ratio 27.81 27.14
• Elderly dependent ratio 22.16 25.14
23. Five key indicators
27
• Crude Birth Rate (CBR) – number of live births per 1,000 people
CBR= (Births/Population) x 1,000
• General Fertility Rate (GFR) - total number of live births per 1,000 women of
reproductive age (ages 15 to 49 years)
GFR= (Births/Female population) x 1,000
• Age Specific Fertility Rates (ASFRs) - the number of live births per 1,000
women in a specific age group usually in 5 year age intervals
ASFRaged x = (Birthsaged x/Female populationaged x) x 1,000
24. Five key indicators
28
• Total Fertility Rate (TFR) – finding the approximate magnitude of ‘completed
family size’ by summing age specific fertility rate for all ages; if 5-year age
groups are used, the sum of the rates is multiplied by 5.
TFR= 5(∑ ASFR) x 1,000
TFR =2.1: Replacement level.
• Gross Reproductive Rate (GRR) - the average number of girls that would be
born to women living through the child bearing ages (15-49 years), assuming
no mortality
GRR = 5(∑ ASFR_girls)
25. Population and Births in 2009
29
Age groups
Total pop.
aged 15-49 Female pop. Male pop. Total Births Births (girls)
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284
45-49 4,889,621 2,523,521 2,366,100 1,266 595
Total 36,175,778 18,163,626 18,012,152 760,349 368,152
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
26. Fertility in Thailand in 2009
30
• Crude Birth rate (CBR) =
• General Fertility Rate (GFR) =
• Age Specific Fertility Rates (ASFRs)women ages20-24 =
• Total Fertility Rate (TFR) =
• Gross Reproductive Rate (GRR) =
27. Population and Births in 2009
29
Age groups
Total pop.
aged 15-49 Female pop. Male pop. Total Births Births (girls)
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284
45-49 4,889,621 2,523,521 2,366,100 1,266 595
Total 36,175,778 18,163,626 18,012,152 760,349 368,152
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
CBR= (Births/Population) x 1,000
• Crude Birth rate (CBR) = 11.97 (12 births per 1000 pop.)
28. 29
Age groups
Total pop.
aged 15-49 Female pop. Male pop. Total Births Births (girls)
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284
45-49 4,889,621 2,523,521 2,366,100 1,266 595
Total 36,175,778 18,163,626 18,012,152 760,349 368,152
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
Population and Births in 2009 GFR= (Births/Female population) x 1,000
General Fertility Rate (GFR) = 23.59 (24 births per 1000 women ages 15-49)
29. 29
Age groups
Total pop.
aged 15-49 Female pop. Male pop. Total Births Births (girls)
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284
45-49 4,889,621 2,523,521 2,366,100 1,266 595
Total 36,175,778 18,163,626 18,012,152 760,349 368,152
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
Population and Births in 2009
ASFRaged x = (Birthsaged x/Female populationaged x) x 1,000
Age Specific Fertility Rates (ASFRs)women ages20-24 = 79.14 (79 live births for every 1000 women ages 20-24)
30. 29
Age
groups
Total pop.
aged 15-49
Female pop. Male pop. Total Births Births (girls) ASFR
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126 ?
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096 ?
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078 ?
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853 ?
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120 ?
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284 ?
45-49 4,889,621 2,523,521 2,366,100 1,266 595 ?
Total 36,175,778 18,163,626 18,012,152 760,349 368,152
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
Population and Births in 2009
TFR= 5(∑ ASFR) x 1,000
31. 29
Age
groups
Total pop.
aged 15-49
Female pop. Male pop. Total Births Births (girls) ASFR
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126 0.05
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096 0.079
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078 0.0783
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853 0.0577
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120 0.027
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284 0.007
45-49 4,889,621 2,523,521 2,366,100 1,266 595 0.0005
Total 36,175,778 18,163,626 18,012,152 760,349 368,152 0.2995
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
Population and Births in 2009 TFR= 5(∑ ASFR) x 1,000
Total Fertility Rate (TFR) = 1.50 (1.50 births per woman)
32. 29
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
Population and Births in 2009 GRR = 5(∑ ASFR_girls)
Age groups
Total pop.
aged 15-49
Female
pop.
Male pop. Total Births Births (girls)
ASFR
(girls)
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126 ?
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096 ?
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078 ?
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853 ?
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120 ?
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284 ?
45-49 4,889,621 2,523,521 2,366,100 1,266 595 ?
Total 36,175,778 18,163,626 18,012,152 760,349 368,152
33. 29
Age groups
Total pop.
aged 15-49
Female
pop.
Male pop. Total Births Births
(girls) ASFR
15-19 4,910,411 2,390,695 2,519,716 119,828 58,126 0.0243
20-24 4,721,027 2,326,086 2,394,941 184,096 89,096 0.0383
25-29 5,244,631 2,597,929 2,646,702 203,386 98,078 0.0378
30-34 5,422,374 2,711,644 2,710,730 156,397 75,853 0.0279
35-39 5,535,275 2,810,343 2,724,932 76,340 37,120 0.0132
40-44 5,452,439 2,803,408 2,649,031 19,036 9,284 0.0033
45-49 4,889,621 2,523,521 2,366,100 1,266 595 0.000236
Total 36,175,778 18,163,626 18,012,152 760,349 368,152 0.145
Total populationall age = 63,525,062 (Male=31,293,096 Female=32,231,966)
Population and Births in 2009 GRR = 5(∑ ASFR_girls)
Gross Reproductive Rate (GRR) = 0.73 (0.73 female births per woman or 730 female births per 1000 women)
34. Fertility in Thailand in 2009
• Crude Birth rate (CBR) = 11.97 (12 births per 1000 pop.)
• General Fertility Rate (GFR) = 23.59 (24 births per 1000 women ages 15-49)
• Age Specific Fertility Rates (ASFRs)women ages20-24 = 79.14 (79 live births for
every 1000 women ages 20-24)
• Total Fertility Rate (TFR) = 1.50* (1.50 births per woman)
• Gross Reproductive Rate (GRR) = 0.73 (0.73 female births per woman or 730
female births per 1000 women)
31
* Lower than the replacement level (2.1 births per woman)
37. Three key indicators
34
• Crude Death Rate (CDR) - the number of deaths per 1000 people
= (Deaths/Population) x 1,000
• Age Specific Death Rates (ASDRs) - total number of deaths to population of a
specified age or age group
= (Deathsage x /Populationage x) x 1,000
• Infant Mortality Rate (IMR) - number of deaths per 1,000 live births of
children under one year of age
= (Deathsage 0 /All births) x 1,000
38. Population and deaths in 2009
35
Age groups Total Population Deaths
0 752,321 5,416
0-4 3,973,721 7,476
5-14 8,918,024 4,003
15-34 20,298,443 30,999
35-59 23,100,621 107,484
60+ 7,166,630 243,785
Unknown - 169
Total 63,457,439 393,916
1. CDR
2. Age Specific Death Rates (ASDRs)age35-59
3. Infant Mortality Rate (IMR)
39. Mortality in Thailand in 2009
36
• Crude Death rate (CDR) = 6.21 (6.2 per 1,000 pop.)
• Age Specific Death Rates (ASDRs)age35-59 = 4.65 (5 per 1,000 pop. of that
age)
• Infant Mortality Rate (IMR) =7.12 (7 deaths of infants under age 1 per 1,000
live births)
41. Migration indicators
38
• Must consider about geographic and time dimensions
• May vary according to specific context and people
42. Keywords
39
• Immigration
– the process of people entering a foreign country to live
• Emigration
– the process of people leaving a country to live in another
• In-migration
– the process of people moving into a new area in their country to live
there permanently
• Out-migration
– the process of people moving out of an area in their country to
another area in their country permanently
43. Types of indicators
40
• International migration
– Crude immigration rate
– Crude Emigration rate
– Crude net migration rate
– Crude gross migration rate
• National migration or internal migration
– In-migration rate
– Out-migration rate
– Net migration rate
– Gross migration rate
44. Types of indicators - International migration
41
• Crude immigration rate
= (Number of immigrants/Total population at destination)*k
• Crude emigration rate
= (Number of emigrants/Total population at destination)*k
• Crude net migration rate
= (Number of immigrants - number of emigrants)/ Total population at destination)*k
• Crude gross migration rate
= (Number of immigrants + number of emigrants)/ Total population at destination)*k
47. Source: Migration survey in 1994 (October-December) Table 8, Page 84. NSO
45
Population and migrants classified by previous
and current place of residence in 1994
Current
region
Previous region Total
migrants
Total
population
Bangkok Central North Northeast South
Bangkok - 157,958 158,443 630,426 38,547 985,374 5,739,369
Central 61,335 - 89,657 317,968 24,922 493,882 4,892,055
North 40,408 60,269 - 56,261 8,815 165,753 11,965,435
Northeast 147,329 134,007 29,573 - 15,131 326,040 21,463,562
South 34,368 19,013 34,619 85,852 - 173,852 8,466,272
Total
Migrants 283,440 371,247 312,292 1,090,507 87,415 2,144,901 6,256,693
48. Source: Migration survey in 1994 (October-December) Table 8, Page 84. NSO
45
Current
region
Previous region Total
migrants
Total
population
Bangkok Central North Northeast South
Bangkok - 157,958 158,443 630,426 38,547 985,374 5,739,369
Central 61,335 - 89,657 317,968 24,922 493,882 4,892,055
North 40,408 60,269 - 56,261 8,815 165,753 11,965,435
Northeast 147,329 134,007 29,573 - 15,131 326,040 21,463,562
South 34,368 19,013 34,619 85,852 - 173,852 8,466,272
Total
Migrants 283,440 371,247 312,292 1,090,507 87,415 2,144,901 6,256,693
In-migration rate (to BKK) ?
Out-migration rate (from BKK) ?
Out-migration rate (from BKK)
Mo= (Outmigrants/Population)*k
(283,440/5,739,369)*1000
=49.4
In-migration rate (to BKK)
Mi= (In-migrants/Population)*k
(985,374/5,739,369)*1000
=171.7
• In-migration rate
Mi= (In-migration number/Total population)*k
• Out-migration rate
Mo= (Out-migration number/Total population)*k
49. 1. What demographic indicators
can be calculated from the
number in the Gazette?
2. Please calculate the
demographic indicators that
you specify in Question 1.
(round your answer to two
decimal places*)
*If the number at the next decimal place is five
or more add 1 to the previous decimal place.
QUIZ
48