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How The Numbers of Babies Affect A Women's Yearly Income

Posted by Maliya Edwards in Statistics · Isakowitz · A on Tuesday, January 31, 2017 at 11:18 pm

Maliya Edwards


1/16/17


Ms.I


Benchmark




You ever wonder what could affect the amount of money you make in a year? You ever wonder why you make the amount of money you do and what's stopping you from making more? There are many answers and variables that affect your annual money a year. Today we are focusing on the amount of children and the amount of people in a family effect has on the amount of money made each year. All which support the idea of the less amount of family members and children can lead you to make more money.

In the early 1800s, Ghana were having nearly 7 kids per woman. The family size was an average of 9. In the 1800s Ghana average 696 a year. Now back in the 1800s there weren't a lot of jobs and there wasn't a lot of good paying jobs. Seen below As we get further into the future, in the 1900s Ghana average family size was 8 and the average amount of children were 6. At this time the average amount of money made a year was 725. During the 1800s Ghana were going through diseases. It lowered the amount of the population. It may not show in the average size family but a lot of people died due to diseases. As we get into the 2000s, Ghana average family size went down to 6 per family and roughly about 4 to 5 children a family. At this time people in Ghana were making up to 2,270 a year. Seen belowAs better jobs and vaccines came out for these diseases. As we go into the year 2015, the average family size went down to 5 and the average children per woman went down to 3 roughly 4 kids and average an amount of 4,100 a year. From the 1800s Ghana family size was 9 and average children in the family were 7, now in 2015 the average family size is 5 and children within the family is 3. Seen below

The next country we are looking at is Keyna. In the 1800s Kenya family size was 9 and average children to a family was 7. Again around this time there wasn't a lot of jobs anywhere let alone jobs that paid a good amount of money. People in kenya in the 1800s made roughly 854 a year. Seen below Compared to ghana the family and children size were about the same, although Kenya made more money a year than Ghana. As we get closer to the 1900s Kenya was another country to deal with diseases and deaths throughout the years. In 1900s Kenya family size was still roughly around 9 and children per family was still hovering around 7. The money per year did go up to 1,170 a year. At this time people in Kenya were all at work. Kids started work a very early age to support their families. As deaths started to go up, more education and better jobs were being built. In the 2000s Kenya family size was down to 7 and babies per woman down to 5. The average salary a year has also gone up to 2,140 as seen below Kenya economy started to get better and were offering better paying jobs to the people. Seen below In 2015 Kenya family size went down to 6 per family and 4 children per woman. They were also making 2,900 a year as seen below As the year went on Kenya people had less children and were making more money.

As we move along we take a look at the United States. In the 1800s there was 7 children to a family and average family size was 9. United States was making 2,130 a year. Seen below As we get to the 1900s, we know United States was going through slavery and wars. This made the country lose a lot of people to death and there wasn't many jobs. Most jobs were war or being a slave. In the 1900s the United States the family size plumbed down to the size of 5 to a family and roughly 4 kids to a woman. United states also made 6,820 a year. That was a big jump from 1800 to 1900. As we get closer to the 2000s, United States have gotten their freedom, have rebuild and structure the country and got better jobs. The family size went down again to 4 a family and 2 children to a woman in 2000s. They also made roughly 46,000 a year. Seen below In 2015 the family size and children to a woman and still the same but with the country advancing in technology it made nearly 53,400 a year. Seen below United States has and still known for the richest country in the world.

The last country we are going to look at is China. To start off China made 985 a year with a family size of 7 and children size a 5 in 1800s. Seen below In the 1900s diseases also spread through China wiped out most of its country. China family and children size were still the same trying to refill its population again. They made 894 a year, less than what they made in the 1800s. In 2000s China made roughly 3,680 a year. The children to a woa went down to 2 and family size to 4. The family size dropped very big because China passed a law saying women couldn't have more than 2 babies. Seen below As we get to 2015 the average family size was 3 and the average kid to a woman was a 1 and they also made up to 13,400 a year seen below.

While doing this paper I realize the more kids people had the less time they spent working which mean the less money they made a year. With children you have to spend so much time taking care of them while they are young which meant you couldn't always go to work. In a lot of cases, people in these countries lost their jobs when they had a big family because they miss work too much. All in all, i do believe the less children you have the more money you will make.





The Sources I used was from the YouTube video from class https://youtu.be/N-x7eHuUhNM and  https://www.google.com/amp/nypost.com/2016/01/03/how-chinas-pregnancy-police-brutally-enforced-the-one-child-policy/amp/





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Life Expectancy VS Employment Rate

Posted by Anaiah Davis in Statistics · Isakowitz · A on Sunday, January 29, 2017 at 9:58 pm

Anaiah Davis

Marina Isakowitz

Statistics

January 2017


Many people around the world believe that in some countries, there are both low rates of employment and life expectancy, due to factors of unemployment leading to lower life expectancy. Studies have shown that “Poorly educated women that were unemployed were also more likely to die earlier” (Groth). It’s a thought process that seems to be correct, but it lead me to wonder: if unemployment affected life expectancy, did employment change how long people lived as well? I wanted to see if having a job/career affected how long a human would live. Although it seem that there should be a solid relationship between employment rate and life expectancy, my research has shown there is no correlation between these two categories, and this shows in countries especially like the Philippines, Trinidad and Tobago, and The Congo, where the two variables do not correlate at all.

Before I could begin, I had to create graphs on the website Gapminder. One graph would have a world view using my two variables, employment rate for individuals 15 and older and life expectancy, and the next graph would only have the three countries I’ve chosen (Trinidad and Tobago, The Philippines, and The Congo). In both graphs, the x axis is the percentage of individuals 15  and older who are employed, and the y axis is the life expectancy in years. The size of the bubbles represent the population size, and so judging by the second graph (Graph 1.2), you can tell the Trinidad and Tobago has the smallest population while the Philippines has the biggest population size of all 3 countries. The color of the bubbles represent the region each country is, and so based off this information, in the second graph the Philippines are in Asia (red), the Congo is in Africa (blue), and Trinidad and Tobago is in the Americas (green). Screenshot 2016-12-20 at 10.12.06 PM.png


In the first graph, we can see that most countries are in the middle in terms of employment rate, and are pretty high in terms of life expectancy. There are a few African countries that are very high in terms of employment rate, even though they don’t have the highest life expectancy, and this is due to increased youth job employment in African countries and more “young people are trying to find more productive work” ("New Report Outlines Priorities To Address Africa’S Youth Employment Challenge"), although not a lot of people are living longer.Screenshot 2016-12-20 at 10.19.59 PM.png

In graph two, we first analyze Trinidad and Tobago. As the percentage rate of employment in the country continuously increased (from 45% to 62.6%), the life expectancy has stayed a bit constant, raising ever so slightly at times. This means that the country has seen much more people working in recent years, but the life expectancy has barely moved from its place.

For the Philippines, the employment rate has decreased and increased multiple times during the years, making a zigzag like pattern on the graph, while the life expectancy barely moved an inch. A year where the employment rate went quite south was the year 2000, and this made me ponder why so many individuals were unemployed in 2000, and what caused the non-constant employment rate in the country. One reason for the fluctuating employment rate during the 90’s was due to the Philippines 2000 economic reform, implemented by then President Fidel Ramos, with the goal of the dismantling of cartels and monopolies, opening up of domestic industries to foreign competition, lowering of tariff barriers to stimulate competition and reduce incentives to smuggling, and de-regulation of certain graft-prone sectors. Although met with opposition from the business interests and government personalities, this could be a key reason on why the employment rate for the Philippines was everywhere.

In terms of the year 2000, which saw a steep decline in the employment rate, this was due to the trial of President Joseph Estrada, who was “charged with plundering more than $80m from state funds while in office (Philippines Profile- Timeline)”. This year is when most Filipinos struggled with poverty, rebellion from Muslim groups, “and lawlessness amid accusations of corruption, cronyism, and economic failure.” The unemployment rate at this time was also high, “and economic growth, at one of the lowest rates in the region, was insufficient to raise the rapidly increasing population from poverty (Bradsher)” and due to the ongrowing economic problems, a stock market scandal, and guerrilla challenges, foreign investment was discouraged, and it was needed to help the economy grow. However, the employment has slowly been rising over the past few years, which is a good sign, but this helps prove the point that life expectancy does not correlate with the employment rate.

In the Democratic Republic of the Congo, there was a steep drop in 1996 in terms of life expectancy, and it continuously dropped and increased. Even with the drops, the employment rate wasn’t affected as I thought it would, which brings me to the question on what happened in 1996 that cause a sudden drop in life expectancy and why didn’t it affect the employment rate that much (it moved about .1 percent). The reason for this was due to the first and second Congo wars. It became with a genocide, where “Hutu-power groups (called the Interahamwe and the Impuzamugambi) led mass killings of Tutsis and pro-peace Hutus, murdering 800,000 people in approximately 100 days (Zapata)”.  Due to the murdering of so many people, about 2 million refugees poured into the Congo from the western border of Rwanda, mostly Hutu, and “They terrorized and robbed the local population with impunity until October 1996, when eastern Congolese Banyamulenge (Tutsi) led an uprising to force the Rwandans out of the Congo, sparking the First Congo War.” Since there were 2 wars (1996-2003), this could be the strongest reason on why the life expectancy in the country fluctuated as much as it did.

Based on my research and what I know about the correlation between employment rate and life expectancy, individuals could survive in countries without a job (it doesn’t affect how long they can live),  and although employment rate could be higher than expected, that doesn’t mean that everyone is prospering and living longer in that country. And it proven in countries that reside in Africa, and my personal three countries.
















Works Cited

Bradsher, Henry. "Philippines In 2000". Encyclopedia Britannica. N.p., 2000. Web. 15 Jan. 2017.

Groth, Aimee. "Being Unemployed Could Shorten Your Lifespan". Business Insider. N.p., 2017. Web. 18 Jan. 2017.

"New Report Outlines Priorities To Address Africa’S Youth Employment Challenge". World Bank. N.p., 2014. Web. 19 Jan. 2017.

"Philippines Profile - Timeline - BBC News". BBC News. N.p., 2017. Web. 15 Jan. 2017.

Zapata, Mollie. "Congo: The First And Second Wars, 1996-2003 | Enough Project". Enoughproject.org. N.p., 2017. Web. 15 Jan. 2017.


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Sierra Leonean woman and Italian woman's life expectancy when living with HIV

Posted by Lucia Idriss in Statistics · Isakowitz · A on Saturday, January 28, 2017 at 12:28 am

Lucia Idriss

01/10/17

Mrs. I

Statistics




There is no correlation between HIV and life expectancy in females within the countries of Sierra Leone and Italy.HUMAN IMMUNODEFICIENCY VIRUS ( HIV) "Unlike some other viruses, the human body can’t get rid of HIV completely. So once you have HIV, you have it for life. HIV attacks the body’s immune system, specifically the CD4 cells (T cells), which help the immune system fight off infections. If left untreated, HIV reduces the number of CD4 cells (T cells) in the body, making the person more likely to get infections or infection-related cancers. Over time, HIV can destroy so many of these cells that the body can’t fight off infections and disease. HIV is an easily contracted disease that can be transmitted through breast milk, sexual activities, and also blood.Countries such as Sierra Leone are underdeveloped and do not have access to all the resources needed to sustain incurable diseases such as HIV, whereas Italy has that kind of access because they are a more developed country.  I wanted to learn more about those whom have been infected and why they’ve been infected. To truly determine what the data points on the graph represent, from the least to the greatest. So now I will test whether your location and income affect the life expectancy in women with HIV.

When I first began I asked myself questions such as : How many of these women were sexually active before marriage and where these women sexually abused to contract HIV? So I took those questions to the web to find out that, yes sexual abuse was used as a form for some of these woman to contract HIV, especially in Sierra Leone during the war time. As I searched around even further I came an article ( lifeinitaly.com ) says “ In the past sex was viewed as a taboo subject. In Italy, like so many other European countries, this was perhaps mostly due to the powerful influence of the Catholic Church on Italian society. Sex was not a topic discussed by people in public, nor did it have a presence in the media.” and “ The average age for the first sexual experience is currently 17 in Italy. This is a difference of up to four years compared to the past, in particular the 30's-40's, when women generally had sex for the first time when they were, on average, 21-22 years old. Not only has the age for first experience changed but so has the context.” So could this also be a reason as to why HIV has such a high testing rate in Italy? Yes. And that evidence can be found on the gapminder graph that I have created.

The graph on gapminder tells a story of the women in Italy and Sierra Leone living with the HIV disease. In the graph you can clearly see that there is no positive nor negative correlation between the two countries. But you can also see that Italy has a larger bubble and also a longer life expectancy than women in Sierra Leone. The bubble represents the amount of women infected by the HIV disease, but how is it that they are living longer than the women who actually have  a lower HIV infection? Poverty, many women in Sierra Leone live in poverty, they are not expected to live as long because treatment in sometimes non affordable so they wind up passing because they can no longer take care of themselves. But as for the women in Italy they are more financially equipped so they can then actually take care of themselves to live much longer. The graph’s story has been told as to what the bubbles and correlations represent.

Now I also asked myself “ does living circumstances affect treatment availability? “ and my answer to that is yes. Some people who have been diagnosed with HIV cannot afford treatment because they are too poor, but based off of the graph that seems to have not affected the life expectancy for those women whom have been diagnosed. But in recent affairs I have noticed that the graph in 1990 Italy’s life expectancy increased, and there must have been a more affordable access to the treatment. This same increase also happened in Sierra leone in 2000 and remained at that same rate in 2006 going forward. So I believe the same affect that happened in Italy also Happened in Sierra Leone.  

In conclusion, from my research I can say that HIV does affect life expectancy in Females, and I can conclude that your financial statement also plays a part in whether or not you will receive treatment for the HIV disease. But I can still remain to say that there is no correlation on the graph determining life expectancy and HIV in Sierra Leone and Italy.  


Screen Shot 2016-12-19 at 8.42.33 AM
Screen Shot 2016-12-19 at 8.42.33 AM
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Women with HIV/AIDS affects on the death rate.

Posted by Imani Mumin in Statistics · Isakowitz · A on Friday, January 27, 2017 at 11:15 pm

https://youtu.be/LJScSCyIbis

Imani Mumin

Mr. I

1/16/17

Research Paper




More than 36.6 million people in the world have been infected with HIV/AIDS and about 35 million have died from it. Many people are diagnosed with HIV/AIDS but women are drastically infected with this disease. Though over time statistics has shown that death rates due to the infection has decreased. I feel like this is an important topic to focus on because not many people in society focus on just women health. Women are all together are infected with this disease more than men. Today women are unaware of the extreme measure of this disease and I think throughout my paper they could be well informed of the this disease and how the women HIV/AIDS rate effect the death rate. Not only women but everyone should be caution of tis disease and how harmful it is.



Most people get infected with HIV/AIDS through sexually transmitted diseases but that isn’t the only way. Studies have shown that people can get infected if the virus gets inside of someone's bloods cells. You can get it through mouth, vaginal area, anus, penis or any wounds from the skin. Out of all the ways possible to get HIV/AIDS women mainly gets it from sexual intercourse. Today, of all 36.7 million people with this disease more than half are women. The website AVERT which contains global information about HIV/AIDS say that there were an estimated 380,000 new HIV infections among young women ages 15 to 49 every year. Meaning that the death rate will most likely double every year due to HIV/AIDS rates.

Screenshot 2016-12-21 at 11.43.48 AM.png



Back than death rates due to HIV/AIDS were higher than they are now all over the world. Based off of the graph I created on gapminder today the death rate of women have dropped largely because of new health resources and wealth. Once people gained the resources to be safe during sex and proper aid for sickness and any other diseases the death rate dropped. Also because countries are becoming wealthier which helps people pay for medical help to try to stay alive as long as possible. In the article HIV/AIDS by the website AVERT it says “Out of all 36.7 million people with AIDS today about 22.6 million die from it globally when before more than half died.” This information shows the dramatic change between the death rate between the times periods.



Screenshot 2016-12-21 at 11.19.18 AM.png




Women living with HIV will have the same health issues as men living with HIV but women are likely to face greater challenges. This can include trying to take care of a family, finding the best medical treatment and living with society's opinions. Although HIV/AIDS is a disease that is guaranteed to kill someone there are ways to help slow the disease's progress and prevent secondary infections and complications. In the article HIV/AIDS by the U.S. Department of Veterans Affairs it says “People who are getting treated for the disease are taking 3 or more drugs.” These drugs attacks the virus in their own ways but they prevent the virus from making copies of itself. This treatment may not cure the virus but it is a good way to help people enjoy the rest of their life knowing they can live a while longer.




In conclusion HIV/AIDS is a virus that have a large effect on women's lives but I they have a great support system and resources to health, money and education then they have better ways to prevent themselves from getting the virus. This is an important topic because people don’t really pay attention to how this disease have a greater effect on women than it does to men. Based off of the information I included we can see that overall women may have gained these resources because the death rate dropped which mean that less women are dying and becoming better with preventing themselves from getting HIV/AIDS.
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How does Child Mortality Rates Affect Life Expectancy?

Posted by Nzinga Hutchinson in Statistics · Isakowitz · A on Friday, January 27, 2017 at 10:39 pm

StatisticsResearchPaper
https://youtu.be/Xvi1PuCCw5w
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Talib's TED talk

Posted by Talib Coffield-Zaboor in Statistics · Isakowitz · A on Friday, January 27, 2017 at 5:52 pm

http://www.youtube.com/watch?v=uyCzSrf-hhk

Taalib Coffield

Ms.Isakowitz

1.10.17

Statistics



Suicide is the third leading cause of death for people ages 15-24 all over the world according to the Centers for Disease Control and Prevention. I researched how a country’s average income affects the country’s suicide rates. Within my research I found out some important information that is useful and informative. Through graphical analysis, I have found that there is no major correlation between suicides being high amongst high income countries and vice versa. There is also no major correlation between high suicide rates amongst low income countries. I found out that middle income countries have an exceeding high suicide rate. Through my research, I will try to explain how other resources were wrong when they came to the conclusion suicide rates are the highest amongst high income countries. Instead I’ve found rates to be the highest in middle income Countries based off of my evidence I found that to not be true, also I will explain why the suicide rates are what they are in each income country. The hope is to gain knowledge of how does income affect the low, middle, and high income countries.





       Low income countries are fairly accused of having high suicide rates because they’re low in the economic level according to Huffington Post. Also, In many resources from Huffington Post. I found it is more common that high suicide rates come from high income countries. As I did my own research I started to realize that that wasn’t the occasion anymore.Based off of graphical analysis, suicides do happen in Low income Countries however, the most suicides do not come from low income countries as many believed before.  There is some level of suicide rates in the low  income countries, and my question is why? During my research I seen that Afghanistan was a low income country that had a low suicide rate, but still had a suicide rate. The income of Afghanistan in the year 2002 was $647dollars with a suicide rate of 5.4 per 100,000 people. According to my Gapminder Graph.

( Figure 1 )

Screenshot 2017-01-19 at 1.11.37 PM.png


This proves that many people think that there were massive amount of suicides within the low income countries. However, based off of Afghanistan and later research, I can say that this rate is kind of low. Still I wonder to myself why are there 5.4 per 100,000 suicides still? Many of the suicides that happen in Afghanistan mainly come from women who have been forced into marriages, that is rape victims, and that is victims of domestic violence. Based off of “Report: Suicide Deaths in Afghanistan Higher Than Murders, War Deaths Combined by Edwin Mora” Looking at the graph you see a tiny increase in the amount of suicides of 10 people from 2003 to 2004. Suicides are bad no matter how much the number of people are, however looking at my graphs and correlating it to other resources has enlightened me. There are not as many suicides in low income countries than there is in middle or high income countries.




          High income countries are what you can call the wealthiest. The country that has the most money, but does that mean the more money higher the suicide rates? Like many articles I have read for instance “ Why Are Suicides More Common In Richer Neighborhoods” by Josh Sanburn have said that most suicide rates come from people with more money. Now this may be talking about neighborhoods or people,  however neighborhoods coexist within a country, and people coexist within the neighborhood which will ultimately means the same thing. Now based off of graphical studies ( Figure 1)  I have seen that in many of the wealthiest countries I researched there is not an over exceeding amount of suicides.  Reading the article ( Why Suicides Are More Common in Richer Neighborhoods )you would think that Suicides basically only come from those people who have a higher income and nowhere else really. However, I found that to not be true. I have found that  suicides are high in high income countries, but they do not have the HIGHEST suicide rates like many acclaim. United States was the richest country of the countries I researched. I found that the United States have an income of 15,300, while it has 11.2 suicides per 100,000 people in the most recent year: 2004. ( Record: Figure 1 ) It has been made clear that STILL high income countries don’t have the highest amount of suicides, but they still have a pretty large amount. Suicide rates have jumped tremendously in the last 30 years according to “U.S. Suicide Rate Surges to a 30-Year High” by Sabrina Tavernise. Women in their middles ages tend to be the biggest group that suffer from suicides. I will say it affects women in their middle age the most normally during this time Women start to become mothers, go though manipulate and it creates a mid life crisis. This is what leads many Women to suicide. Through research I have gathered, especially in the United States who has the highest income suicide rates come from mid life crisis. Not because so many Rich people get tired of their life as Josh Sanburn implied in his article. Suicide rates are high in The United States, but they are not high as one other country.



      China is a middle income country that has an income per person of $5,680. The suicide rate however is 16.9 per 100,000 people. As I was hinting in my other graph analysis’s, suicide rates are the highest in the MIDDLE income countries. Now this is surprising because many other articles have swore up and down that High income countries, and low income countries have had the highest suicide rates. ( According to sites below. ) While in my research I have seen that that is not the case, it is the total opposite in fact. China is one of the highest suicidal countries in the world. ( Figure 1 ) It mainly comes from Women as it does in many other countries. Although, the reasons behind it is different. Women in China tend to commit suicide because many women are stressing, and people have diseases such as bronchitis and cancer. That causes women to end their life because of the pain and infliction they go through. This is shocking to me because so many articles I’ve read has said middle income countries aren’t really the ones affected by income. I personally think that this happens in middle income countries because the middle tries to live a higher income life acting as if they are rich, while kind of in reality many people still have an income that relates more to the low income pool of things. This makes a lot of sense, because they seem to stress between the two lives of high income and low income. It makes people become stressful, which may lead to being overwhelmed that may cause suicide. Along this graph I was able to see that the income level with the most suicides come from a middle income level instead of low or high.



           In conclusion, I have proved that Suicide rates are most excessive in the middle income countries instead of the high and low income countries. There has been multiple articles ( at the bottom of page )  that seems to think that middle income countries are the least of worries. My research has told me otherwise. Depending on the different countries you decide to study in depth, my conclusion may change but in these circumstances my theory remains.



Work Cited:


http://www.suicide.org/suicide-statistics.html#death-rates

http://www.nytimes.com/2016/04/22/health/us-suicide-rate-surges-to-a-30-year-high.html?_r=0

http://www.cnn.com/2016/04/22/health/suicide-rates-rise/


http://business.time.com/2012/11/08/why-suicides-are-more-common-in-richer-neighbor

hoods/

http://www.sras.org/how_does_income_affect_suicide_rates

http://www.huffingtonpost.com/2012/11/09/suicide-rate-rich-neighborhoods_n_2102777.html


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TED TALK : How does HIV/AIDS affect life expectancy?

Posted by Jada Martin in Statistics · Isakowitz · A on Friday, January 27, 2017 at 4:27 pm

https://youtu.be/mXc_KCAKeJI

Jada Martin

Ms. I

Statistics

1/16/17

“How does having HIV/AIDS affect life expectancy?”



HIV is an infection that attacks the body’s immune system, specifically the CD4 cells (T cells), which help the immune system fight off infections. If left untreated, HIV reduces the number of CD4 cells (T cells) in the body, making the person more likely to get infections or infection-related cancers and can lead to AIDS(“What is HIV/AIDS?”, 2016).  HIV/AIDS weakens the body and presents a pathway for opportunistic diseases such as tuberculosis, pneumonia, and meningitis(Loewenson and Whiteside4). The HIV/AIDS widespread is one of the most devastating health crises of modern times, ruining families and communities throughout the world(Ashford1). Life expectancy is defined as the average number of years that a person can expect to to live in. Stigma, globalization, and human development are the three main focus for why these specific countries have low life expectancy levels.

Human development is basically about gaining  freedom and opportunities and improving your well-being. It is about creating an environment in which people can develop their full potential and lead productive, creative lives in accord with their needs and interests. Making sure human development has an approach to HIV/AIDS helps to focus on the study of people rather than on the virus.  HIV/AIDS is affecting the Human Development Index (HDI). The index measures basic human capabilities, ranking countries according to their average levels of life expectancy, educational attainment and basic purchasing power(Womenaid International1).  Researchers have concluded that the world lost on average 1.3 years of human development progress due to the pandemic between 1982 and 1992 (Womenaid International1).

AIDS is both a product and a cause of globalization. Globalization affects all  of human life, including health and well being. The HIV/AIDS epidemic has pointed out the global nature of human health and welfare and globalization has given rise to a trend toward finding common solutions to global health challenges. HIV/AIDS is affecting the global human development of African countries through its devastating impact on health and demographic indicators such as life expectancy at birth, healthcare assistance, age and sex distribution.  By 2005, more than 25 million people had died and an estimated 39 million were living with HIV. An estimated 4 million people were newly infected with HIV(Ashford1).  Countries that have been hard hit by the AIDS epidemic have seen mortality surge and life expectancy drop in the last decade. Such as Sub-Saharan Africa, Eastern Europe, and Asian countries. When looking at the graphs below you’ll be able to see this impact.

Screenshot 2017-01-16 at 10.33.38 PM.pngScreenshot 2017-01-16 at 4.59.55 PM.png

HIV/AIDS was discovered 1981; the virus, 1983. These Gapminder bubbles show you how the spread of the virus was in 1983 in the world, or how it was estimated.  In the graph the y axis represents the life expectancy and the x axis are represented by people living with HIV total of all ages. The total number of people in all ages that are estimated to be infected by HIV, including those without symptoms. The life expectancy represents the average numbers of years a newborn child would live if current mortality patterns were to stay the same. The bubbles represents the country and the size of the bubbles represent the population of the country. As the x value changes the y values increases which indicates that it’s a negative correlation. The graph is pretty consistent as it’s increasing there aren’t any outliers. As you can see in the first graph when it was first discovered only a few countries had the disease the life expectancy was still at an average rate. Around 1987 the graph starts to decrease a lot which means that the people with HIV started to increase and the life expectancy decreased in the countries. As you can see in the graph when HIV/AIDS has already increased and affected countries China has the biggest population size which means the more people affected the lower the life expectancy is for that given country.

HIV/AIDS is related back to stigma because it refers to prejudice, negative attitudes and abuse directed at people living with HIV and AIDS. In 35% of countries with available data, over 50% of men and women report having discriminatory attitudes towards people living with HIV(AVERT1).  Some people are pushed away by family, peers and the wider community, while others face poor treatment in healthcare and educational settings, no basic human rights, and psychological damage. These all limit access to HIV testing, treatment and other HIV services. For example, A man living with HIV in China filed a lawsuit in 2012 after he was denied a job as a primary school teacher when the employer found out he was HIV-positive. That’s where the low life expectancy comes in because people start to die off because they aren’t getting the fair treatment that they need.

Some people may argue that HIV/AIDS isn’t the cause of low life expectancy. Life expectancy refers to the expected number of years of life remaining for an individual at a given age. Overall there are several factors, including sex, race, and lifestyle habits, are known to influence life expectancy. One of the biggest factors that people may say is the cause of low life expectancy is drugs. Drugs have been the main cause for suicide for decades. People have so manys ways to obtain drugs and they overdose and die. So, others don’t blame diseases and infections for the reasons that people are dying off.

HIV/AIDS is a personal, social and economic tragedy as well as a global health threat.  In Europe and North America, AIDS is now the leading cause of death for adults under 45(The Global HIV/AIDS Epidemic1). The above statement is the main reason why I decided to focus on the HIV/AIDS epidemic. People overall aren’t very aware in my opinion of the spread of HIV/AIDS. Even though I didn’t focus more so on North America but HIV/AIDS is definitely on the rise because so many people ignore the fact that this disease is real and incurable. While doing this essay I learned a lot about globalization and the stigma of people who are affected by this.















MLA CITATION

General Topic: How HIV is affecting the world

http://www.prb.org/pdf06/howhivaidsaffectspopulations.pdf

Ashford, Lori. "How HIV and AIDS Affect Populations." HOW HIV AND AIDS AFFECT POPULATIONS (n.d.): n. pag. BRIDGE. Population Reference Bureau. Web. <http://www.prb.org/pdf06/howhivaidsaffectspopulations.pdf>.


General Topic: Statistics on HIV

http://www.healthline.com/health/hiv-aids/facts-statistics-infographic

Heitz, David. "HIV by the Numbers: Facts, Statistics, and You." Healthline. George Krucik, n.d. Web. 21 Dec. 2016. <http://www.healthline.com/health/hiv-aids/facts-statistics-infographic>.


General Topic: How has HIV impacted families

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2822872/

Ji, Guoping, Li Li, Chunqing Lin, and Stephanie Sun. "The Impact of HIV/AIDS on Families and Children -a Study in China." AIDS (London, England). U.S. National Library of Medicine, Dec. 2007. Web. 21 Dec. 2016. <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2822872/>.



General Topic: Global epidemics on HIV/AIDS

https://www.aids.gov/hiv-aids-basics/hiv-aids-101/global-statistics/

"Global Statistics." Welcome to AIDS.gov. U.S Department of Health & Human Services, n.d. Web. 21 Dec. 2016. <https://www.aids.gov/hiv-aids-basics/hiv-aids-101/global-statistics/>.



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  • Marina Isakowitz
Science Leadership Academy @ Beeber · 5925 Malvern Ave · Philadelphia, PA 19131 · Ph: 215-400-7270 Fax: 215-400-7271
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