Question

What are the health risks that are prevalent in each of the age groups. Look at interventions to increase health living with each group and the role the community health nurse plays.

Answer 1

Health risks in age group:

Children In 2011–2014, the prevalence of children with obesity among those aged 2–5 years was 8.9%, 17.5% among children aged 6–11, and 20.5% among adolescents aged 12–19 . In 2014, 4.9% of adolescents aged 12–17 reported smoking cigarettes in the past month. Smoking prevalence has declined since 2004, when 11.9% of adolescents reported smoking cigarettes in the past month

. Adults In 2014, 20.9% of adults aged 18 and over met the 2008 federal physical activity guidelines for both aerobic activity and muscle strengthening . Between 1999–2002 and 2011–2014, the percentage of adults aged 20 and over with Grade 1 obesity (a body mass index [BMI] of 30.0–34.9) increased from 17.9% to 20.6%. Those with Grade 2 obesity (BMI of 35.0–39.9) rose from 7.6% to 8.8%, and those with Grade 3 obesity (BMI of 40 or higher) increased from 4.9% to 6.9% (percentages are age-adjusted) . In 2014, 16.8% of adults aged 18 and over were current cigarette smokers, a decline from 2004 (20.9%). Men (18.8%) were more likely than women (14.8%) to be current cigarette smokers in 2014

1. Goal This presentation was made in hopes of teachingstudents how to properly evaluate their communitypopulation in order to better asses community healthissues.
2. 3. ObjectivesUpon completion of this presentation, students would be able to: Define community health and related terms. Identify the three main factors effecting community health. Understand the steps necessary for community organizing.
3. 4. Understanding Your Community Community: a group of people who have common characteristics definable by location, race, ethnicity, age, occupation, interests in particular problems or outcomes, or common bonds. (Source: McKenzie, Pinger, Kotecki, 2012). (Source: CardCow, 2011)
4. 5. Determinants of Population Race Black, White, Hispancic Nationality/Ethnicity German, Haitian, Iranian, American Sexual Orientation Male or Female (Strait, Gay, Lesbian) Age or Age Group 2yrs, 15yrs, 65yrs (Toddler, Teen, Elderly) Geographic locality St. Petersburg Florida
5. 6. Population Chart: St. Pete White 66.5% Black 24.9% American Indian 0.4% Asian 3.7% Pacific Islander 0.12% Hispanic 7.1% Two or More Races 2.9% Other Race Origin 1.6% (Source: Stpete, 2011) (Source: Stpete, 2011)
6. 7. What is Community Health? Community Health: is the status of a defined group of people and the actions and conditions to promote, protect, and preserve their health. Population Health: is the health status of persons not organized and without identity as a group or locality.
7. 8. Understanding a Community In order to evaluate one’s community, one must understand the factors that effect the health of a community. The three main factors and determinants of community health are as follows: 1. Physical Factors 2. Social and Cultural Factors 3. Individual Behaviors (Source: McKenzie, Pinger, Kotecki, 2012)
8. 9. Factors of Community Health Physical Factors: Examples: Geography Dry,Tropical Environment Smoggy, (polluted) Community Size 244,000 Industrial Development Metropolitan, Rural
9. 10. Factors of Community Health Contd. Social and Cultural Factors: Traditions, Prejudices, Beliefs Economy Politics Socioeconomic Status
10. 11. Business and Education Charts Average Household $58,711 Income Income Education Median Household $45,903 Income Per Capita Income (PCI) $26,130 (Source: Stpete, 2011) Arts, Culture, Events, Tourism 564 Marine Science 1,842 Manufacturing 5,278 Industry Hospitality (Food & Lodging) 7,810 Information Technology 8,200 Financial Services 16,054 Medical Technologies & 18,778 Healthcare Services (Source: Stpete, 2011) (Source: Stpete, 2011)
11. 12. Individual Behavior Individual Behavior: The behavior of the individual community members contributes to the health of the entire community. (Source: McKenzie, Pinger, Kotecki, 2012) Herd Immunity Concept
12. 13. Community Organizing Community organizing: To find methods and procedures to help deal with social issues within the community. Example: Cancer from tobacco use is a social health issue in St. Petersburg. Therefore community organizing would involve methods and procedures to deal with the issue such as canvasing or an awareness campaign.
13. 14. Community Organizing Process Recognize the Issue Gain Community Entry Organize People Asses the Community Set Goals and Priorities Arriving at a Solution(Source: McKenzie, Pinger, Kotecki, 2012).
14. 15. Community Organizing Process Contd. Selecting Strategies Implementing Plans Evaluating outcomes Maintaining outcomes Looping Back(Source: McKenzie, Pinger, Kotecki, 2012).
15. 16. Questions1. Which of these Determinates of Population are based on one’s place ofbirth or home country?A. RaceB. GeographyC. AgeD. NationalityE. Sexual OrientationNationality is usually determined by one’s place of birth or at least thecountry they consider home. Race is not an issue because a person ofHaitian or German decent could be born in any country. A Black, White,and Hispanic American all have the same nationality.
16. 17. 2. According to the US Census Bureau (2010), the population of thecommunity of the city of St. Petersburg is approximately 244,000consisting of roughly 70% white, 24% black, and 5% Hispanic. TheIndustry section inside the Business and Education Chart states thenumber of Medical Technologies & Healthcare Services personnel inSt. Petersburg, FL. What is the percentage of the population that is inthat industry?A. About to 7.5 %B. .0812C. .0647D. About to 6.8 %E. .0711The correct answer is 0.0769590163934426 or about to 7.5%.18,778 / 244,000 = 0.0769590163934426
17. 18. 3. Which of these are NOT considered part of the communityorganizing process?A. Gain Community EntryB. Set Goals and PrioritiesC. Conduct a DebateD. Asses the CommunityE. Recognize the IssueConducting a debate is a way in which one may asses the community.The debate may bring up views and needs of community members.However, debates can also dismantle one’s cause or agenda due to theuncontrollable nature of debates. Debates can cause even the mostgifted speaker to take defensive standpoint that may deter listenersfrom aligning with the agenda.Conducting an open discussion with community members give thecommunity organizer more control of the flow of the conversation.
18. 19. 4. Community health is the health status of persons notorganized and without identity as a group or locality.T/FFalse: Community health is the status of a defined group ofpeople and the actions and conditions to promote, protect, andpreserve their health.Public health is the health status of persons not organized andwithout identity as a group or locality.
19. 20. 5. From the information about past racial tension of St. Petersburgpresented in the Social and Cultural Factor section how would thisinfluence your community organizing process?My community organizing process would be affected by this in thatas I gain community entry and organize people, I am aware ofnotions, beliefs and prejudices that may arise. I may decide to asklocal historical authorities or research the events that took place.From examining how the Uhuru, local police and businessesclashed, I would make certain that I do not offend any party withthe community organizing

Community Helath nurse role increase health living:

while several indicators are commonly used to monitor the public’s health, life expectancy is perhaps the most widely used and best recognized. Life expectancy is the average number of years lived by all members of a population [9]. It is extremely useful when comparing the relative health of populations from different locations and time periods. The indicator is by no means a new concept; life tables have been used to evaluate life expectancy since the days of John Graunt (1662) in England [10].

Numerous conceptual models have been used to account for the factors that determine health and life expectancy. In the 1970s, the LaLonde report proposed that life expectancy was the result of lifestyle, the physical environment, medical care, and biological factors [11]. Critics suggest this model only views proximate health determinants and ignores the more distal, but nevertheless powerful broader social influences on health [12]. Contemporary health determination models include these broader contributing factors such as poverty, education, housing, food insecurity, unemployment, and income distribution [13,14]. These more holistic models emphasize the ecological nature of multiple health determinants, which interact to form a “web of causation” explanation of health and life expectancy.

Not all health determinants are equally important. The Health Impact Pyramid developed by Frieden postulates [15] that both addressing socioeconomic factors and changing the social/environmental context of health-related decisions have the greatest ability to increase life expectancy. Despite these recommendations, the United States spends almost 18% of its gross domestic product (GDP) on technologically-oriented healthcare, and underfunds cost effective public health programs that have been proven to improve population health [16].

The predilection to improve health through medical interventions may partially result from not knowing that major life expectancy gains in the last 200 years were primarily the result of improvements in nonmedical determinants of health [1-5]. Historical analysis indicates that improved sanitation in the form of public water treatment, sewage management, food inspection and municipal garbage collection nearly eliminated the diseases of cholera, dysentery and typhoid [17]. Revolutionary methods of agricultural production, food transportation, and preservation greatly improved the average diet eradicating many nutritional deficiency-caused diseases and improving immune function against infectious diseases [18]. In 1900, tuberculosis was the number two cause of death in America [1]. Better housing, less crowded living conditions, and improved nutrition tremendously reduced this disease long before the first effective TB drug was developed in 1946 [19]. Approximately half of the reduction of the coronary death rate in the last 50 years is attributed to lifestyle improvements, which primarily reduced tobacco use [20,21]. Unintentional injury and occupational deaths rates were significantly reduced through regulations, education and engineering changes [22]. Air quality has improved with the elimination of coal burning furnaces, leaded gasoline and better industrial emissions regulation [23]. More education, higher literacy rates, child labor laws, and increased economic prosperity also greatly improved life expectancy and health [5,24-26].

As a result of these improvements in nonmedical determinants of health, and in combination with advancements in healthcare, life expectancy increased from approximately 39 years in the mid-1800s to nearly 79 years by 2014. [27,28]

The Center for Disease Control and Prevention estimated in 1999 that 25 of the 30 years of increased life expectancy in the United States in the Twentieth Century were attributed to advances in public health [1]. McKinlay and McKinlay calculated that only 3.5 of the total mortality decline between 1900 and 1970 could be “ascribed to medical matters” [25]. Bunker calculated that clinical prevention and therapeutic interventions could be credited with five and a half of the thirty-year increase that occurred in the United Kingdom from 1900 to 2000 [29]. Hence, public health interventions and improved social conditions can take most of the credit for the increase in life expectancy experienced since the mid-1800s.

Methods

Population

Analyses are based on a representative cross sectional survey of the U.S. adult population. The distribution of selected demographic variables was similar between survey participants and the U.S. population.

Sample

Survey data were gathered from an online sample of actively managed panels of high quality respondents who have been recruited by a large professional public opinion/marketing research company called Survey Sampling International [30]. The online sample involved respondents from the United States who were willing to provide their honest opinions. The company’s reward system engaged and motivated participation and encouraged better representation. Participants who have an interest in contributing to research were incentivized to be members of the company’s response panels. The strict quality control procedures used by the company’s recruiting practices ensures that samples of opt-in respondents are of high quality. The demographics of potential respondents were known to the research company before an invitation to participate was extended. The opportunity to complete the survey was progressively closed to some potential respondents after select demographic variables were sufficiently represented in the sample. This procedure ensured that the generated sample was representative of the United States national demographic profile with respect to age, sex, race, income, and education. A total of 725 individuals completed the survey.

Quality assurance methods were used to identify nonsensical survey responses. Twenty such responses were eliminated from the analysis, resulting in a final sample size of 705.

Instrument

A questionnaire was developed to assess what factors the public believes contributed to the increased life expectancy and health improvements over the past two centuries in the United States. Three public health faculty, separate from those on the current study, evaluated the instrument for content and face validity. This resulted in a revised version of the questionnaire that was then tested on a convenience sample of twenty individuals who were thought to be representative of the U.S. adult population. This resulted in a few additional minor revisions, following which the instrument was administered to a group of 357 public health students. Based on the hypothesis that the majority of people would attribute the increase in life expectancy to medical care instead of public health prevention, an effect size and standard deviation was obtained from the pilot study group to calculate the required sample size. Human subject approval to conduct the survey was obtained from the research team’s academic institution.

The survey utilized questions that provided three alternative measurements of how people explain the historical increase in life expectancy. The survey begins with a statement that “This survey deals with health, disease and life expectancy. Life expectancy is defined as the average number of years people will live from birth. Future life expectancy is the number of years the average person will yet live after reaching a certain age.” They were then asked in an open-ended question, as follows: “In the United States, average life expectancy was 35 years in 1850 and 79 years in 2011. What is the single biggest reason for this improvement in life expectancy?” Responses were independently coded by two researchers into the categories of “modern medicine,” “better nutrition,” “healthier lifestyle,” “sanitation,” “education, awareness, knowledge,” and “other/don’t know.” The responses were numerically coded and the few discrepancies (n=7) that occurred were recoded after discussion and mutual agreement.

Second, participants were given a list of six factors that public health historians suggest were major causes for life expectancy increase since the mid-1800s. This second measure of attribution provided plausible explanations which participants may not have recalled and, therefore, considered when answering the open-ended questions. The question asked was: “Several factors have contributed to the rise in life expectancy seen in the U.S. from 1850 to the present day. Below, rank each factor by its level of contribution to the rise in life expectancy. 1= the most important factor, 2= the second most important factor, and so forth until you reach 6= the least important factor.” The factors to be ranked were improved sanitation, improved food production, vaccinations, modern medicine (surgeries, medications, diagnostic techniques, etc.), reduction in poverty, and public education. These first two questions only allowed for a ranking of explanations to be calculated.

Third, the proportion of improved life expectancy people attributed to healthcare/modern medicine was assessed. Participants were informed that the nation spent 17% of its Gross Domestic Product in 2011 on healthcare/modern medicine (e.g., physicians, hospitals, clinics, diagnostic technology surgery, and antibiotics). They were then asked “What would life expectancy be if we spent nothing on healthcare/modern medicine.”

Demographic data were collected to ensure that a representative sample had been drawn and to analyze potential differences in responses between groups. Demographic variables included age, sex, race, ethnicity, income, and education attainment.

Statistical Techniques

Frequency distributions were used to summarize and describe the data. Bivariate analyses were used to evaluate the relationship between selected variables, with the chi-square test used to evaluate significance. The Mantel-Haenszel (MH) chi-square was also used to evaluate differences in trend. Two-sided tests of hypotheses were evaluated using the 0.05 level of significance. Analyses were performed using the Statistical Analysis System (SAS) software, version 9.3 (SAS Institute Inc., Cary, NC, USA, 2010).

Results

Participants are characterized according to selected demographics in Table 1. Sixty-four percent of participants were younger than age 50. There was a slightly higher percentage of females than males, and most were white, non-Hispanic. Fifty-five percent had an income of less than $50,000 per year and 63% had less than a college degree.

	No.	%
Age (years)
18-29	159	23
30-39	146	21
40-49	140	20
50-59	138	20
60-69	90	13
70+	32	5
Sex
Male	344	49
Female	361	51
Race
White	599	85
Black/African American	59	8
Other	47	7
Ethnicity
Latino/Hispanic	57	8
Not Latino/Hispanic	645	91
Don’t Know/Not Sure	3	0
Annual Household Income		0
Less than $25K	171	24
$25K-$49,999	218	31
$50K-$74,999	140	20
$75K or more	176	25
Education
Some High School	15	2
High School Graduate or GED	151	21
Some College or Technical School	282	40
College Graduate	177	25
Master’s Degree	64	9
Doctoral or Professional Degree	16	2
Source: Survey Sampling International, 2012.

Table 1: Summary of participant characteristics.

Responses to the open-end question, which asked participants to identify the single most important reason for increased life expectancy, were most commonly classified as “modern medicine” (Table 2). Far fewer responses were classified as “improved lifestyle,” or “improved nutrition,” and fewer still were classified as “education, awareness, or knowledge” or “improved sanitation.”

Life Expectancy	No.	%
Modern Medicine	462	66
Improved Lifestyle	67	9
Improved Nutrition	62	9
Education, Knowledge	15	2
Improved Sanitation	14	2
Other, Don’t Know	85	12
Source: Survey Sampling International, 2012

Table 2: Open-ended Responses for Explaining Increased Life Expectancy.

Participants were asked to rank from high to low the relative importance of six factors that have been cited in the literature as playing key roles in increasing life expectancy (Table 3). The reason most commonly selected as most important for increased life expectancy was modern medicine. Other factors, such as vaccination and sanitation were much less likely to be ranked first. Education, poverty, and food production combined only received 20% of the first place votes. Bivariate analyses assessed whether selecting modern medicine as the most important reason was associated with age, sex, race, ethnicity, education, or annual household income. Only race was statistically significant, with 45% of whites selecting this item as most important compared with 32% of non-whites (p=0.0151).

Life expectancy	No.	%
Modern Medicine	302	43
Vaccination	141	20
Sanitation	120	17
Education	72	10
Poverty	43	6
Food Production	27	4
Source: Survey Sampling International, 2012.

Table 3: Primary reasons given for the improvement in life expectancy

When asked to project what life expectancy would be if society had all the modern conveniences (e.g. sanitation, education, sufficient income and food production), with the exception of “healthcare/modern medicine,” the average response was approximately 47 years. This would be a decline of 32 years from our current life expectancy of 79 years. These data indicate that of the 40-year life expectancy increase since the mid-1800s, the public attributes 80% of the improvement to modern medicine and only 20% to all other factors.

Discussion

The results of this study show that adults in the U.S. attribute 80% of the improvement in life expectancy since the mid-1800s to modern medicine. The combined impact of improved sanitation, literacy, housing, health behaviors, food production, safer environments, and other public health factors received relatively little credit. These misperceptions were consistently observed across the levels of age, sex, race, education or income.

This study has important implications for a nation that far outspends all others on healthcare, despite a life expectancy ranking in 34nd place [30]. Prudent national health policy that seeks to increase life expectancy and lower healthcare costs should better appreciate the importance of multiple determinants of health. An incorrect understanding of the contribution of public health measures may have resulted in poor policy decisions and distorted funding priorities.

The 2011 World Health Organization Rio Conference report challenged nations to improve health by addressing social health determinants [31]. Unfortunately, when people believe increased life expectancy is primarily the result of technology intensive medicine, they may be more willing to expend a large portion of the national budget on the healthcare sector of the economy. Consequently, fewer resources are available to conduct population-based public health interventions and address social health determinants that improve health, with primary emphasis on prevention.

Many factors might explain the public’s failure to accurately attribute the reasons for improved life expectancy in the United States and elsewhere. Most importantly, society may have simply forgotten. It has been over ninety years since the end of the first public health revolution (1880-1920). Many people today have no personal knowledge of it and, consequently, no fear of many of the diseases that were prevalent at the time, such as cholera, tuberculosis, dysentery, typhoid, rickets, or scurvy. Further, they have little appreciation for how these health problems were solved.

The media may play a role in causing the misperceptions identified in this study. Television programs dramatize and glamorize the world of modern medicine and portray healthcare as having amazing powers to restore health [32]. Television dramas seldom communicate to viewers that environmental factors, poverty, housing, food insecurity, education or social welfare, are powerful predictors of health. In addition to the entertainment function of television, new drugs and medical procedures are also consistently given great attention in broadcast news. By contrast, public health interventions are successful when things do not happen. By definition, the news media does not report on things “not happening.” As a result, the public inflates the relative importance of modern medicine in relation to other health determinants.

Another reason for imbalance of credit for increased life expectancy is that the benefits of medicine are individualized rather than population-based. Medicine treats individual patients who can see the causal connection between treatment and outcomes. Results are also often seen in a short time frame. Patients know they have been helped and are grateful. In contrast, the cause-and-effect link between a public health program and improved health often occurs in the distant future and, therefore, difficult to see. The beneficiaries of public health programs are often unaware that they have been helped [33]. As a result, there is little or no sense of gratitude and relatively little support for funding public health programs.

It is not known whether the under-attribution of credit to the nonmedical health determinants is a belief that can be readily changed. Future research should determine if educational interventions can correct the misperceptions and blind spots identified in this study.There are two limitations that may have influenced the survey results. The survey was conducted online and, therefore, excluded individuals who had no access to computers. People with less education and lower income may be underrepresented in this study. The study was also conducted only in English and excluded a portion of some minority groups.

Conclusion

People are largely ignorant of the factors that have been responsible for increasing life expectancy. The misperceptions identified in this study have implications for national health policy. The society that fails to understand that improvements in nonmedical determinants of health were primarily responsible for past increases in life expectancy may be less likely to support contemporary interventions and policies which seek to address these important but less visible health determinants. Public health workers have the formidable and important challenge of helping the medically-mesmerized public understand that many factors, outside the walls of hospitals, have a profound influence on life expectancy. Health education’s role in public health needs to expand from the focus on individual decision-making. The most fundamental objective of health education is to help society [34] understand what factors contribute most to increased life expectancy and [35] that by addressing those factors, society has the greatest potential to improve the nation’s health.