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H388 Presentations 11/28/06
H388 Presentations 11/28/06
REFUGEES
REFUGEES
What is a Refugee
What is a Refugee
Source : UN Statistics Report 2005: Global Refugee Trends
Source : UN Statistics Report 2005: Global Refugee Trends
Refugee Status is by nature UNEQUAL to nationals of host countries
Refugee Status is by nature UNEQUAL to nationals of host countries
Refugees in Africa
Refugees in Africa
DEPENDENCE OF REFUGEES
DEPENDENCE OF REFUGEES
QUESTIONS GET COMPLICATED Who is the Refugee
QUESTIONS GET COMPLICATED Who is the Refugee
Understanding The Affordable Housing Crisis
Understanding The Affordable Housing Crisis
The Problem
The Problem
H388 Presentations 11/28/06
H388 Presentations 11/28/06
Homelessness is a Poverty Issue
Homelessness is a Poverty Issue
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
The Homeless Population
The Homeless Population
Demographic Factors: Race
Demographic Factors: Race
H388 Presentations 11/28/06
H388 Presentations 11/28/06
Demographic Factors: Geography
Demographic Factors: Geography
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
An Underlying Cause: The Lack of Affordable Housing
An Underlying Cause: The Lack of Affordable Housing
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
An Underlying Cause: The Lack of Government Spending
An Underlying Cause: The Lack of Government Spending
H388 Presentations 11/28/06
H388 Presentations 11/28/06
An Underlying Cause: The Lack of Public Awareness and Support
An Underlying Cause: The Lack of Public Awareness and Support
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
Assessment and Analysis of Nutritional Status in Bangladesh
Assessment and Analysis of Nutritional Status in Bangladesh
Findings
Findings
Example
Example
The Double Burden of Malnutrition
The Double Burden of Malnutrition
The Evidence
The Evidence
Why the Link
Why the Link
Case Study: Washington DC
Case Study: Washington DC
Grocery Stores and Poverty
Grocery Stores and Poverty
Availability and Race
Availability and Race
Why?
Why?
First Obesity, Then Diabetes
First Obesity, Then Diabetes
No Such Thing as an Easy Solution
No Such Thing as an Easy Solution
Dynamics of Poverty Among the Indigenous Population of Bolivia
Dynamics of Poverty Among the Indigenous Population of Bolivia
H388 Presentations 11/28/06
H388 Presentations 11/28/06
Introduction
Introduction
What defines indigenous
What defines indigenous
Historical Factors
Historical Factors
Geo-Economic Factors
Geo-Economic Factors
Mobility Factors
Mobility Factors
Discrimination Factors
Discrimination Factors
Educational Factors
Educational Factors
Educational Factors (Cont
Educational Factors (Cont
Health Factors
Health Factors
Improvements
Improvements
I n e q u a l i t y in B r a z i l Melissa Teixeira
I n e q u a l i t y in B r a z i l Melissa Teixeira
I n e q u a l i t y
I n e q u a l i t y
E d u c a t i o n
E d u c a t i o n
E d u c a t i o n
E d u c a t i o n
M i g r a t i o n
M i g r a t i o n
S o c i a l M o b i l i t y
S o c i a l M o b i l i t y
Poverty, Inequality, and Nigerias Oil Economy
Poverty, Inequality, and Nigerias Oil Economy
Contribution of Agriculture and Oil to Nigerias GDP
Contribution of Agriculture and Oil to Nigerias GDP
Nigerias Principal Agricultural Export Commodities
Nigerias Principal Agricultural Export Commodities
Oil Revenue Distribution 1963
Oil Revenue Distribution 1963
Oil Revenue Distribution 1979
Oil Revenue Distribution 1979
Poverty in Nigeria
Poverty in Nigeria
Yuehong Lei
Yuehong Lei
Maternal Education and the Relationship to Childrens Health
Maternal Education and the Relationship to Childrens Health
Topic
Topic
Personal Findings
Personal Findings
Outline
Outline
Decline in GDP Per Capita
Decline in GDP Per Capita
GDP Per Capita and Female Literacy
GDP Per Capita and Female Literacy
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
H388 Presentations 11/28/06
GDP Per Capita
GDP Per Capita
GDP Per Capita
GDP Per Capita
Conclusion
Conclusion
Manisha Thapa
Manisha Thapa
Variables in Womens education versus Child health relationship
Variables in Womens education versus Child health relationship
Variables in Womens education versus Child health relationship
Variables in Womens education versus Child health relationship
Case for Nepal
Case for Nepal
Programs to improve maternal and child nutritional status
Programs to improve maternal and child nutritional status
Examples of Interventions
Examples of Interventions
Earthwatch Educate women about nutrition and hygiene as related to
Earthwatch Educate women about nutrition and hygiene as related to
Conclusions
Conclusions
Poverty & Female Mental Health
Poverty & Female Mental Health
Issue of Causation
Issue of Causation
Selection Hypothesis
Selection Hypothesis
Social Causation Hypothesis
Social Causation Hypothesis
Previous Findings & Links
Previous Findings & Links
Residing in low-income neighborhoods
Residing in low-income neighborhoods

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1 H388 Presentations 11/28/06

H388 Presentations 11/28/06

Michael Franklin Manisha Thapa Susan Krissel (absent with illness) Ashlyn Murphy

Catie Broussard Kris Van Voorhis Jessica Bruno Elizabeth Schlossberg Amanda Graham Melissa Teixeira Brian Kelly Yuehong Lei (no slides)

2 REFUGEES

REFUGEES

Catie Broussard, 28 November 2006

Dependent, Un-Free, Homeless, Unequal

3 What is a Refugee

What is a Refugee

International Law and Normative Practice dictates that a refugee is a person who owing to a well-founded fear of being persecuted for reasons of race, religion, nationality, membership in a particular social group, or political opinion, is outside of the country of his nationality, and is unable to, or, owing to such fear, is unwilling to avail himself of the protection of that county. ( UN Conventoin,1951) By concentrating on the large refugee populations in Africathose refugees that have being displaced within their home region and are hosted by a neighboring statewe can target the greatest unequal and dependent populations to determine how their living. Policy Questions for Hosts and International Community: Integration vs. Segregation and Repatriation vs. Assimilation Decisions based on the situations of Refugee creation Host or contracting countrys government acceptance of the international treaties and norms vs. indigenous acceptance of new and inherently needy populations

4 Source : UN Statistics Report 2005: Global Refugee Trends

Source : UN Statistics Report 2005: Global Refugee Trends

5 Refugee Status is by nature UNEQUAL to nationals of host countries

Refugee Status is by nature UNEQUAL to nationals of host countries

Uprooted to another country Persecuted Homeless Dependent on Host and International Community

6 Refugees in Africa

Refugees in Africa

Obtained from ReliefWeb

7 DEPENDENCE OF REFUGEES

DEPENDENCE OF REFUGEES

8 QUESTIONS GET COMPLICATED Who is the Refugee

QUESTIONS GET COMPLICATED Who is the Refugee

Do only the poor become refugees? How does the extreme poverty of refugee populations compare to the state of indigenous populations? How can we understand and combat the problems of these dependent, homeless, unequal, un-free populations, that is only further complicated by the difficulty of obtaining statistics and measures of their plight?

9 Understanding The Affordable Housing Crisis

Understanding The Affordable Housing Crisis

Kris Van Voorhis History 388 Hunger, Poverty and Market Economy Professor Ludden November 28, 2006

10 The Problem

The Problem

The American Planning Association has dubbed the affordable housing crisis as a silent killer, likening it to high blood pressure acute, growing, deadly, and yet largely unknown for most Americans According to the U.S. Department of Housing and Urban Development, more than 11 million households fall within HUDs "worst-case" category, forced to pay more than one-half their incomes for housing, endure overcrowded conditions and/or live in structures with severe physical deficiencies. More than 3.5 million Americans are considered homeless, 1.35 million of them being children

11 H388 Presentations 11/28/06
12 Homelessness is a Poverty Issue

Homelessness is a Poverty Issue

13 H388 Presentations 11/28/06
14 H388 Presentations 11/28/06
15 H388 Presentations 11/28/06
16 The Homeless Population

The Homeless Population

17 Demographic Factors: Race

Demographic Factors: Race

18 H388 Presentations 11/28/06
19 Demographic Factors: Geography

Demographic Factors: Geography

20 H388 Presentations 11/28/06
21 H388 Presentations 11/28/06
22 An Underlying Cause: The Lack of Affordable Housing

An Underlying Cause: The Lack of Affordable Housing

23 H388 Presentations 11/28/06
24 H388 Presentations 11/28/06
25 H388 Presentations 11/28/06
26 An Underlying Cause: The Lack of Government Spending

An Underlying Cause: The Lack of Government Spending

27 H388 Presentations 11/28/06
28 An Underlying Cause: The Lack of Public Awareness and Support

An Underlying Cause: The Lack of Public Awareness and Support

29 H388 Presentations 11/28/06
30 H388 Presentations 11/28/06
31 H388 Presentations 11/28/06
32 H388 Presentations 11/28/06
33 H388 Presentations 11/28/06
34 Assessment and Analysis of Nutritional Status in Bangladesh

Assessment and Analysis of Nutritional Status in Bangladesh

Jessica Bruno History 388 November 28th, 2006

35 Findings

Findings

Comparisons of food intake vs. education level, location (urban/rural), gender, occupation, NGO (benefited/non-benefited) Improvements in intake with primary education completed, urban location, female gender, and cultivators

36 Example

Example

37 The Double Burden of Malnutrition

The Double Burden of Malnutrition

Exploring the link between obesity and poverty and why the correlation exists Elizabeth Schlossberg

38 The Evidence

The Evidence

NHANES Survey 1971-2004 revealed a 50% increased chance of becoming overweight in poor versus non poor families (Miech et al 2006) The prevalence of obesity is significantly higher in poor communities than in affluent communities (Journal of Youth and Adolescence) Variables include age and race

39 Why the Link

Why the Link

Focus: Availability of healthy food Healthcare Adequate education about nutrition and a healthy lifestyle A safe environment for physical activity

40 Case Study: Washington DC

Case Study: Washington DC

Focus on the Availability of Fresh Food

Residents in Wards 7 & 8 where poverty is high and grocery stores are scarce are more likely to suffer from diet-related diseases than residents of the Districts other wards (Hunger Solutions). Obesity prevalence in Wards 7 & 8 is about four times higher than in Wards 2 and 3, which have the most grocery stores and many of the highest community food security rankings in the District. (Hunger Solutions)

41 Grocery Stores and Poverty

Grocery Stores and Poverty

The darker colors represent higher rates of poverty

The dots represent grocery stores that sell fresh food

42 Availability and Race

Availability and Race

Ratio of grocery stores to residents revealed a ratio of 1:3,816 in chiefly white neighborhoods as opposed to 1:23,582 in chiefly African American neighborhoods (Journal for Preventative Medicine 2002)

43 Why?

Why?

Similar problems occur in Philadelphia, Chicago and New York, but why? The RISK is greater than the REWARD Cost is too great to maintain security and to train reliable employees in lower income areas Smaller profit margin due to sales of cheaper goods

44 First Obesity, Then Diabetes

First Obesity, Then Diabetes

The Upper East Side vs. East Harlem

Upper East Side grocery stores were three times as likely to stock diet soda, low-fat or fat-free milk, high fiber bread, fresh fruit and fresh vegetables Those living in East Harlem die of diabetes at twice the rate of people in the city as a whole (New York Times 2006) Sub par health care available in East Harlem leaves residents unable to afford medication for diabetes

45 No Such Thing as an Easy Solution

No Such Thing as an Easy Solution

While the availability of fresh, healthy food in lower income areas is one contributing factor to the problem, other factors include education, healthcare and a safe environment. Until all of these factors, along with government support come together, the problem can not be fixed.

46 Dynamics of Poverty Among the Indigenous Population of Bolivia

Dynamics of Poverty Among the Indigenous Population of Bolivia

Amanda Graham November 28, 2006

47 H388 Presentations 11/28/06
48 Introduction

Introduction

72% of population below poverty line Same proportion of those people are indigenous 60% of population indigenous Social ladder whitens in accordance with class privilege Why? Social Exclusion-denied access to resources

49 What defines indigenous

What defines indigenous

36 Indian tribes recognized by government 2 Main Groups Aymara (20-25%) Quechua (35-40%)

50 Historical Factors

Historical Factors

Spanish Conquistadors Exploitation and Slavery Liberalism (19th Century) Biological Category of Slaves Poverty dates from here Serfdom until 1950s Cant escape Continue to live in rural highlands

51 Geo-Economic Factors

Geo-Economic Factors

Rural/Western Provinces Home to Indigenous population Eastern Provinces Local white/foreign business control Control of natural gas resources/GDP

52 Mobility Factors

Mobility Factors

Geographic landscape creates obstacles for adequate construction Lack of adequate roads that link Eastern and Western provinces

53 Discrimination Factors

Discrimination Factors

White Persona v. Indigenous Persona Deprivation of basic human rights by Government Low Paying Jobs

54 Educational Factors

Educational Factors

Low investment in education Indians dont realize situation Dropout rate Attendance disparity between rich and poor

55 Educational Factors (Cont

Educational Factors (Cont

School attendances relationship with child labor

56 Health Factors

Health Factors

Vulnerable to communicable diseases like cholera and tuberculosis Diseases preventable by vaccines lower in rural population Risks to women during child birth

57 Improvements

Improvements

Increase in education Political activism New government leadership Government recognition of demands of indigenous population Improvement slow-needs continued activism

58 I n e q u a l i t y in B r a z i l Melissa Teixeira

I n e q u a l i t y in B r a z i l Melissa Teixeira

National Statistics: Population: 188,078,227 Infant Mortality: 28.6 deaths/1000 live births Life expectancy at birth: 71.97 years Literacy rate: 86.4% GDP per capita (PPP): $8,300 Percentage below the Poverty Line: 22% Gini Index: 0.59

North Roraima Amap? Amazonas Par? Tocantins Acre Rond?nia

Northeast Maranh?o Piau? Cear? Rio Grande do Norte Para?ba Pernambuco Alagoas Sergipe Bahia

Centre-West Mato Grosso Goi?s Distrito Federal (Bras?lia) Mato Grosso do Sul

Southeast Minas Gerais Esp?rito Santo Rio de Janeiro S?o Paulo

South Paran? Santa Catarina Rio Grande do Sul

59 I n e q u a l i t y

I n e q u a l i t y

Inequalities in power and wealth translate into unequal opportunities, leading to wasted productive potential and to an inefficient allocation of resources [World Bank 2006]

The top ten percent of the Brazilian population control fifty percent of salaried income and the bottom fifty percent account for a mere twelve percent of income.

60 E d u c a t i o n

E d u c a t i o n

Level of Education for Students of Five Years or Older, by Region in 2005

Level of Education for Students of Five Years or Older, by Region in 2005

Level of Education for Students of Five Years or Older, by Region in 2005

Level of Education for Students of Five Years or Older, by Region in 2005

Level (and type) of Education (%)

Level (and type) of Education (%)

Region

Region

Region

Brazil

Northeastern Region

Southeastern Region

Average Years

6.6

5.3

7.3

Pre School

9.42

10.19

9.98

Private School

24.29

25.49

23.80

Public School

75.68

74.51

76.15

Primary Education

61.63

66.04

57.40

Private School

11.02

10.27

13.30

Public School

88.98

89.73

86.67

Secondary Education

17.75

15.32

19.88

Private School

15.00

13.55

16.83

Public School

84.98

86.45

83.12

Higher Education

8.86

5.14

10.90

Private School

73.92

58.49

81.40

Public School

26.08

41.51

18.60

61 E d u c a t i o n

E d u c a t i o n

62 M i g r a t i o n

M i g r a t i o n

63 S o c i a l M o b i l i t y

S o c i a l M o b i l i t y

64 Poverty, Inequality, and Nigerias Oil Economy

Poverty, Inequality, and Nigerias Oil Economy

Questions:

Brian Kelly

Is oil wealth distributed unevenly in Nigeria? What agricultural, environmental, economic, and social effects has oil extraction had on the local communities of the Niger Delta?

1

65 Contribution of Agriculture and Oil to Nigerias GDP

Contribution of Agriculture and Oil to Nigerias GDP

Brian Kelly Nigeria and Oil, 2

Source: Onyige, P.U. Energy and Social Development in Nigeria

66 Nigerias Principal Agricultural Export Commodities

Nigerias Principal Agricultural Export Commodities

Brian Kelly Nigeria and Oil, 3

Source: Onyige, P.U. Energy and Social Development in Nigeria

67 Oil Revenue Distribution 1963

Oil Revenue Distribution 1963

Distribution of Mining Rents and Royalties, 1963 Distributable Pools Account Regional Allocations, 1963

Source: Khan, Sarah Ahmad. Nigeria: The Political Economy of Oil

Brian Kelly Nigeria and Oil, 4

68 Oil Revenue Distribution 1979

Oil Revenue Distribution 1979

Distribution of Mining Rents and Royalties, 1979 Breakdown of Allocation to State Governments, 1979

Brian Kelly Nigeria and Oil, 5

Source: Khan, Sarah Ahmad. Nigeria: The Political Economy of Oil

69 Poverty in Nigeria

Poverty in Nigeria

Nigerian GNP per Capita has steadily fallen since 1980.

The percentage of Nigerias rural population living below the poverty line has risen since 1980.

Source: Anyanwu, John C. Rural Poverty in Nigeria: Profile, Determinants and Exit Paths

Brian Kelly Nigeria and Oil, 6

Source: Khan, Sarah Ahmad. Nigeria: The Political Economy of Oil

70 Yuehong Lei

Yuehong Lei

AIDS and TB in South Africa No slides

71 Maternal Education and the Relationship to Childrens Health

Maternal Education and the Relationship to Childrens Health

Michael Franklin HIST 388

72 Topic

Topic

Establishing a link between a mothers education and the health of her children Difficult, many variables deal with childrens health Community and maternal endowments Has research overstated the benefits of improved maternal education?

73 Personal Findings

Personal Findings

Data comes from the UN Stats website (http://hdl.library.upenn.edu/1017/7058) Took 42 countries and compared: GDP per capita in current US$ (1981-2000) Children under 5 mortality rate per 1,000 live births (1980-2000) Literacy rates in women 15-24 (1981-2004)

74 Outline

Outline

Examined data in three ways: Countries where GDP per capita declined Does a fall in GDP lead to deteriorating conditions and a rise in child mortality? Correlation GDP per capita vs. Mortality Rates Female literacy vs. Mortality Rates Countries with similar GDP per capita How do female literacy and child mortality rates compare?

75 Decline in GDP Per Capita

Decline in GDP Per Capita

17 countries experienced a fall in their GDP per capita Decrease in GDP per capita indicates living standards did not improve, and potentially worsened Despite drop in GDP per capita, child mortality rates decreased everywhere, except Zimbabwe (increased) and Liberia (did not change) Literacy rates among women improved in each country

76 GDP Per Capita and Female Literacy

GDP Per Capita and Female Literacy

GDP per capita vs. Mortality rates R? = 0.3822 Female literacy v. Mortality rates R? = 0.749 Stronger association between female literacy and child mortality than GDP per capita

77 H388 Presentations 11/28/06
78 H388 Presentations 11/28/06
79 H388 Presentations 11/28/06
80 GDP Per Capita

GDP Per Capita

Country

GDP

Female Lit (%)

Child Mortality

Cameroon

1,011 (5)

57.4 (4)

173 (4)

Nigeria

1,167 (4)

45.3 (5)

216 (5)

Ecuador

1,207 (3)

93.7 (2)

57 (2)

Costa Rica

1,381 (2)

96.7 (1)

26 (1)

Turkey

1,487 (1)

79.8 (3)

133 (3)

81 GDP Per Capita

GDP Per Capita

Vietnam has the lowest GDP per capita in 1980 yet one of the lowest rates of child mortality and highest of female literacy

Country

GDP

Female Lit (%)

Child Mortality

Pakistan

443

21.5

153

Yemen

444

11.0

205

82 Conclusion

Conclusion

Education = Good Importance of maternal education Present inequality between men and women Improving a mothers level education has been found to yield greater results than improving her husbands level of education

83 Manisha Thapa

Manisha Thapa

Female Education and Child Health in Nepal

84 Variables in Womens education versus Child health relationship

Variables in Womens education versus Child health relationship

Urban-Rural differences - access to health facilities -access to clean drinking water -transportation

85 Variables in Womens education versus Child health relationship

Variables in Womens education versus Child health relationship

Wealth as a variable -similar relation with child health as mothers education -stronger relation than rural-urban

86 Case for Nepal

Case for Nepal

WHO data for 2001 Under-5 mortality rate (per 1 000 live births) - rural to urban ratio) - 1.7 Under-5 mortality rate (per 1 000 live births) - lowest to highest wealth quintile ratio)- 1.9 Under-5 mortality rate (per 1 000 live births) - mother with no to higher education ratio -2.4 Why does the relationship between womens education and child health still hold for Nepal? Gradual Urbanization Increased per capita GDP undermined by inflation Government spending in education relatively higher than in health sector

87 Programs to improve maternal and child nutritional status

Programs to improve maternal and child nutritional status

Susan Krissel (absent due to illness)

88 Examples of Interventions

Examples of Interventions

UNICEF Fortification of food (ex. Iodization of salt) Supplemental micronutrient formula with RDIs for pregnant/lactating women Education for the empowerment of women Baby-Friendly Hospital Initiative International Code of Marketing of Breast Milk Substitutes

89 Earthwatch Educate women about nutrition and hygiene as related to

Earthwatch Educate women about nutrition and hygiene as related to

disease prevention Involve and train community members/leaders Make community self-sufficient Canada Prenatal Nutrition Program Supplementation Community gardens Gift certificates to buy healthy food Cooking demonstrations and shopping tours Nutrition and Health Awareness Education Budgeting workshops Breastfeeding incentives

90 Conclusions

Conclusions

Various types of organizations are taking action to improve maternal/child nutrition These organizations are mainly focused on improving malnutrition through nutrients, rather than targeting its causes

91 Poverty & Female Mental Health

Poverty & Female Mental Health

Ashlyn Murphy Final Project Hist 388

92 Issue of Causation

Issue of Causation

Is there a causal relationship between poverty and mental illness? Which came first: the poverty or the mental illness?

93 Selection Hypothesis

Selection Hypothesis

Emotional problems that are preexisting predispose a woman to poverty. Mental illness/emotional problems precede poverty.

94 Social Causation Hypothesis

Social Causation Hypothesis

Stresses of poverty and the environment of poverty lead to mental illnesses. Poverty precedes mental illness.

95 Previous Findings & Links

Previous Findings & Links

The following circumstances have been pre-established as common among clinically depressed women: Recent entry in welfare program. Dependent upon welfare. Inadequately employed: marked by unfavorable hours and/or wages. 4. Nonunion employment position.

96 Residing in low-income neighborhoods

Residing in low-income neighborhoods

Residing in neighborhoods marked by drug trade. Having no health benefits. Spending large amount of income on child care.

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