Assignment 1: Demographic Analysis

I live at 383 East, 143rd street and my zip code is 10454. It is an area in which Latinos are the main population. This area is called Mott Haven in which there are many public housing projects. I live in one of the housing project in which my neighbors I can see they are mainly Hispanics and Blacks. Around my specific zip code area, there are different neighborhoods. In addition, even though these neighbourhood are very close to each other, there are still a lot of differences between them. I will focus on the varieties of people’s races that inhabit certain areas of the zip code 10454 and how certain areas have more schools while other areas have more businesses.

Santa Clara County has a growing diverse population regarding age, race, and sexual orientation. There are 1,874,526 residents, with 26.6% are ages 0 to 19, 29.4% are between 20 to 39 years old, 28.3% are between 40 to 59 years old, and 15.7% are 60 years of age and older; specifically, 11% of the total population is seniors aged 65 and over—the priority population (California Department of Finance, 2014). At present, Santa Clara County has the second fastest growing population (1.47%) in 58 counties of California, just behind Alameda County (1.68%) while California’s growing rate is 0.88% (credit). By gender, there are 893,851 males and 887,791 females. Between 2011 and 2012, approximately 31,000 residents

I will first introduce my study and explain why I’m conducting my study and what their responses will be used for.

The demographic transition has been closely accompanied by an epidemiological transition in the area of health, that is, a change in the profile of morbidity and mortality by cause, and the distribution of deaths by age. This transition is apparent in the percentage reduction in deaths caused by transmissible (respiratory, infectious and parasite–borne) diseases and in those in the perinatal period, giving rise to a relative predominance of deaths caused by chronic and degenerative diseases (of the circulatory apparatus and malignant tumors), as well as external causes (caused by violence, accidents and injuries). This reflects both the greater drop in mortality for the first group of causes, which mainly occur in children, as well as by the

The United Kingdom is a nation that has stood the test of time. Through development of technology and healthcare the United Kingdom has brought itself into the modern world offering healthcare services to the people and raising life expectancy. This great nation also was part of the 189 countries that signed the Millennium Development Goals (MDGs)to improve the overall quality of life for the world’s population. Through demographic profiling and research, this paper will examine the health indicators, burden of disease, population, and socioeconomic data and explain the health priorities and goals in relation to accomplishing the Millennium Development Goals.

Demographic change can impact on a slower reduction in TB incidence. Barcelona TB Control Program (PPCTB), Community health workers (CHW), and Public health nursing team (PHNT) also helped improve action procedures for immigrants including monitoring cases and their contact in accordance with international

This Pyramid is similar to Stable Pyramids, but has a lower birth and death rate. Contracting Pyramids have slightly longer life expectancies, and has an older average population in comparison to the Stable Pyramid.

For my information background I will talk about the demographics, soical, economic, housing. First I will start with the demographics on the NYC census factfinder. for the sex the male population is 42.6 percent. For the female population is 52.4 percent, with a total of 100 percent. The higest age range with 17.3% is 25 to 34 years of age. The lowest age range with 1.8% ie 85 years and over. For kid in the area is 5.7% 5 to 9 years of age. Now we have the race population with a total of 100%. Hispanic or latino of any race is 28.7% , Mexican 3.8 percent, puerto Rican 9.0%, Cuban 0.5%, other hispanic or latino 15.3%, not hispanic or latino 71.3%, White alone 33.1%, black or african American 22.7%, american indian and alaska native 0.2%,

Joan is a 70-year-old female that is now retired and living in Kingston, On. Joan and her husband Tom are considered upper class, with their annual household income being over $200,000 a year. Joan was born in March of 1947, and her husband was born in May of 1948. In 2016, Kingston’s population was 172,411. In terms of the gender breakdown, females make up 51.3%, while males are only 48.7% of the population (Kingston Population). Kingston is a major retirement city, with 14.1% of the population at or above the average retirement age. Kingston is also not a very diverse town, with 94.2% of the population identifying as Caucasian (Kingston Population). According to PRIZM, Kingston’s population consists of a 3 major sections,

San Diego has a population of 3,299,521, 49.8% of which are female and 50.2% males. The state population of females is about the same at 50.3%. The percentage of persons under the age of 5 is 6.6% of the population and the percentage of persons under 18 years old is 22.3%. The state population of persons under the age of 5 is the same at 6.5% and the percentage of persons under 18 years old is a little higher at 23.6%. People aged 65 and older make up 12.7% of the population which is slightly lower than the state percentage of 12.9% (United States Census Bureau,

Trends in population have much to do with the planning and dynamics of the delivery of healthcare. Population size and demographic characteristics as well as births and deaths, are a basic starting point for assessing the need for health services in a population (Williams & Torrens, 2008). According to Williams & Torrens (2008), the dynamics of population are the most fundamental determinants of the need, demand, and use of health care services. The size and age composition of a population have a tremendous impact on total health services use as well as on the distribution of the use of specific services.Therefore, trends in population dynamics, including population size and demographic characteristics as well as births and deaths, are a basic starting point for assessing the need for health services in a population (Williams & Torrens, 2008).

All of the three studies agreed on the mean or median age of the patients. However the duration of hospital stay were varied between them; an earlier study reported a longer duration of hospital stay. This can be understood because since 2013, the hospital had introduced a new program called “patient-dropping”, where patients who had been hospitalized for a considerable long time but had no longer had criteria for hospitalization, were sent home by the hospital. This program shorter the duration of hospital stays significantly; from the average 15 month in 2012 to only 6 month in 2014.

For this assignment, I observed people walking through the Michigan campus on a Tuesday afternoon. Since I did not personally know each person who walked by, this demographic could have potentially included students, professors, residents, and/or travelers; however, most of my sample appeared to be students, as they were wearing backpacks. While most of the people looked to be roughly 18-22 years old, the age range of the demographic ranged from adolescents to those in late adulthood. People participated in my situation by walking through my field of observation, which allowed me to observer the issue at hand: if gender affects how people walk through crowds. My role in the situation was two-fold because I took on both the role of a walker and an outside observer. While I was walking, I was interacting with others in ways that potentially affected their walking patterns, but while I was sitting down, I was observing their behavior without

My first demographic variable is “Age”, which is classified as interval level of measurement. The descriptive statistics for age includes the mean which is 2.6093, (SD=.65814) and lastly, the range which is 5.00. Meanwhile, the second demographic variable is “Employment Status”, which is classified as a nominal level of measurement. The descriptive statistics for employment status includes the frequency which is 278 (91.4%) and the mode which is 1.00 for this demographic variable. The last demographic variable is “Ethnicity” and it is once again a nominal level of measurement. We use frequency and mode as out descriptive statistics for this variable. The frequency is 277 (91.1%), but there is no mode for the variable ethnicity. My independent variable asks about gender which is classified as a nominal level of measurement.

Of the demographic data included in Fayette County’s profile, the indicators/variables that best assess how widespread poverty is includes, but is not limited to, population density, lack of high paying jobs, monthly rent, median household income, educational attainment, unemployment, disability with age, reported pregnancies, uninsured persons, mediocre schools, and crime rates (Center for Rural Pennsylvania, 2014).The rationale for selecting these indicators/variables is fairly simple as each indicator/variable is dependent on each other.