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Where We Live Matters: Social Determinants of HIV Risk
1. WHERE WE LIVE MATTERS:
SOCIAL DETERMINANTS OF HIV RISK
Presented by
2. TOPICS TO BE DISCUSSED
• Racial/Ethnic Populations Distribution
• Socio-economic Status
Poverty
Educational Attainment
• Neighborhood Stability
• Crime/Violence
• Theft
• Assault
• Homicide
• STDs
• HIV/AIDS
3. OUR PLACE DETERMINES OUR HEALTH
SOCIAL/
But all of POLITICAL /
these factors ECONOMIC
determine our DEMOGRAPHICS
ENVIRONMENT
place
INCOME
4. WHAT FACTORS IMPACT HEALTH?
• Genetics
• Access to medical care
• Health literacy
• Social networks
• Stress levels/coping mechanisms
• Income
• Social Stigma (racism, sexism, ageism, etc.)
• Education
• Safety/Violence
• Water, air, and soil quality
• Access to healthy foods
• Working conditions
• Transportation
5.
6. SOCIAL DETERMINANTS – WHAT?
Health is impacted by where
we live, work, play and learn
Many factors outside of our
control impact health and
well being
Our early life experiences
affect later health
7. SOCIAL DETERMINANTS
• Social and economic factors are extremely powerful
predictors of death and ill-health across a wide
range of diseases and injuries
• Three distinct components:
– Socio-economic determinants
• Age, sex, education
– Psycho-social risk factors
• Social support, self esteem, chronic stress
– Community and societal characteristics
• Income inequality, level of trust, social capital
9. PSYCHOSOCIAL RISK FACTORS
Poor social networks High physical/
Low self-esteem psychological demand
Self-efficacy Chronic stress
Depression Isolation
Anxiety Anger/hostility
Insecurity Coping
Loss of sense of Perception/ expectations
control
10. COMMUNITY AND SOCIETAL
CHARACTERISTICS
Social networks Poverty
Social and community Residence (urban,
participation rural)
Civic and political Income inequality
involvement Crime rate
Trust in people and Domestic violence
social institutions Unemployment rate
Tolerance of diversity
Altruism, charity work
11. SOCIO-ECONOMIC STATUS AND HEALTH
Association between health and socio-
economic status is causal
Our social and economic status can be the cause of
either declining health or illness/disease
As income/education/status increase, health and well
being increases
(Ansari, Carson et. al, 2003)
12. SOCIAL DETERMINANTS AND HIV
• Where we live affects health and HIV risk behaviors
– Living in a socially disadvantaged neighborhood can
lead to fatalism, risky coping mechanisms (substance
abuse, risky sexual behaviors)
– Some communities have limited or no access to health
information or medical/mental health services
– Social networks impact sexual and drug use behaviors
and health
14. WHO’S IN OUR SOCIAL NETWORK MATTERS
Composition of social networks impacts HIV risk
Individual risk is not determined by personal risk behavior
alone, but also the “pool” of disease in their sexual/drug using
networks
(Augustine and Bridges, 2008; Adimora & Schoenbach, 2005; Aral, Adimora, Fenton, 2008)
15. WHO’S IN OUR SOCIAL NETWORK MATTERS
Composition of social networks impacts HIV risk
Factors impacting the intensity of HIV in a network:
Density – how many people in a network have
had sexual contact with each other
Sorting – tendency of people with similar
characteristics (race, age, neighborhood) to
associate with one another and not others
outside the community
Mixing – when someone has sexual contact with
someone outside their primary network
Concurrent partnerships – having more than one
sexual partner at a time
16. CONCURRENT PARTNERSHIPS
Concurrent sexual partnerships or partnerships that
overlap in time raise HIV transmission risks more
than having multiple consecutive monogamous
partnerships.
Recent research found that African American men
had 2.56 higher odds of engaging in concurrent
relationships as White men.
Poverty, substance use and abuse, and
incarceration are associated with concurrent
partnerships
(Nunn, Dickman, Cornwall, et. al 2011)
17. SEX RATIO IMBALANCE
Some African American communities have more
females than males
Due to high infant mortality and death to violence and
disease, as well as high incarceration rates
Imbalance grows as the population age increases –
more boys for children, less males in elderly population
Imbalance affects behavior of both males and females,
in terms of concurrency and risk behaviors
Women may perceive a shortage of men and tolerate
behavior/risk they might not otherwise
Men have some leverage in relationships, because there are
other women available
18. PHILADELPHIA FACTORS - CONCURRENCY
Philly has the 4th highest incarceration rate in the
U.S. – 5.7 per 100 residents
Nearly 45% of African Americans have never been
married
Fewer than 10% of individuals living below the
poverty line are married
Philly has sex ratio of .82 for African Americans
(Nunn, Dickman, Cornwall, et. al 2011)
20. HEALTHCARE SYSTEM
• Most socioeconomically disadvantaged populations
tend to use more primary and secondary health
services, but make less use of prevention services
like: prenatal care, immunizations, health screening
and dental services
• Primary health services – regular doctor visits
• Secondary health services – treatment of specialists to
manage/cure disease
21. MORTALITY
Black:White ratios of mortality from coronary heart
disease, cancer and diabetes were larger in 1990s
than 1950s.
Researchers at CDC estimated that 38% of the
excess mortality among Black adults compared to
White adults was related to differences in income
Krieger et. al estimated if everyone experienced the
mortality of the wealthiest 20% of Whites, between
1960 and 2002 we would have avoided:
14% of premature deaths among Whites
30% of premature deaths for Blacks
(Williams & Collins, 2001; Woolf & Braverman, 2011)
23. RACIAL/ETHNIC COMPOSITION
Philadelphia population: 1,526,006
White: 626,221 or 41.0 %,
46,893 Male & 66,239 Female below the poverty
level (2009)
Black: 661,839 or 43.4 %
79,976 Male & 111,335 Female below the poverty
level (2009)
Hispanic: 172,483 or 11.3%
31,600 Male & 37,799 Female below the poverty
level (2009)
Asian: 96,405 or 6.3%
Male 9,877 & 9,835 Female below the poverty
level (2009)
(US Census Data)
24. RACIAL/ETHNIC DISPARITIES
Compared with Whites, Black and Hispanics:
Generally
Earn less income and have less schooling
At the same educational level, have lower
incomes
At the same educational/income level, are more
likely to have grown up in disadvantaged
circumstances
At a given income level
Have less wealth (all earnings, properties, investments)
Live in unstable neighborhoods
(RWJF 2011)
25. RACIAL SEGREGATION AND SOCIAL FACTORS
Race may help determine place, but people of different
ethnic/racial groups experience similar health outcomes in
severely disadvantaged neighborhoods
Segregation is the primary cause of racial differences in socio-
economic status (SES)
The worst urban context in which Whites live is better than the
average context for Black communities.
Many segregated areas have high levels of multiple sources
of stress including:
Violence
Financial stress
Family separation
Chronic illness
Death
Family turmoil
(Williams & Collins, 2001; Woolf & Braverman, 2011)
27. EDUCATIONAL ATTAINMENT
Educational attainment affects health through:
Health knowledge
Employment and income
Sense of control
Social networks
People with more education are more likely to:
Live longer
Experience better health outcomes
Practice health-promoting behaviors
Have close friends on whom they can rely
Have greater family stability and supportive marriages
(RWJ, 2011)
28. EDUCATIONAL ATTAINMENT
Residential segregation has led
to highly segregated primary
and secondary schools and is
the fundamental cause of racial
differences in the quality of
education
Children’s health is strongly
linked to their parents’
education, particularly mother’s
29. PHILADELPHIA- EDUCATIONAL ATTAINMENT
80% of Philadelphians 25 years and
older have HS diploma/GED or greater
6% less than 9th grade
13.4% have 9-12th grade
16.6% Some college/no degree
12.8% Bachelor’s degree
9.8% Graduate degree
Philadelphia drop out rate is 3.37% in 2010,
highest in PA
30. POVERTY AND CHRONIC STRESS
Poverty/near poverty is often stressful because so much
time/energy devoted to daily tasks and securing
necessities
Stress can lead to harmful coping mechanisms like
smoking, drug use and risky sex
Chronic stress or stress during critical periods can lead to
illness in adulthood through the neuroendocrine (nervous
system transmitters), immune, inflammatory
pathways/systems
Chronic diseases like diabetes and heart disease
Low birth weight, prematurity
Neuroendocrine problems with lifelong effects (some cancers
(RWJF, 2011)
31. POVERTY AND FAMILIES
Total Married Male Female
Families Couple Householder Householder
Families with no wife no husband
own children present with present with
under 18 own children own children
present under 18 under 18
311,055 64,488 or 13,818 or 64,800 or
20.73% 4.44% 20.83%
Families below 59,827 8,056 or 4,271 or 33,734 or
poverty line in 13.47% 7.14% 56.39%
2009 inflation-
adjusted $
Average Family Income -$45,842 (in 2009 inflation adjusted $’s)
Philadelphia has highest poverty rate of the 10 largest cities
32. THE GAP WIDENS
Between 2005 and 2009 the average net worth
of households decreased considerably:
• Fell by 16%
Whites • From $134,992 to $113,149
• Fell by 53%
Blacks • From $12,124 to $5,677
• Fell by 66%
Hispanics • From $18,359 to $6,325
(Woolf & Braverman, 2011)
34. SOCIAL DISADVANTAGE AND VIOLENCE
People with limited income and social
support/resources are more likely to:
Have social networks which
include others of limited means
and ability to provide support and
comfort
Experience social disorganization
Experience conditions which
deepen feelings of
anger, frustration, hopelessness
which may make it more likely to
resort to violence
Have peers who engage in and
encourage violent responses to
conflict
(RWJF, 2011)
35. LINKS BETWEEN VIOLENCE AND HEALTH
Violence can affect health-related behaviors
Violence-associated stress affects motivation and capability
to adopt and adhere to health-promoting behaviors and/or
increases the use of health-harming coping behaviors
Violence-related stress may lead to poorer health
Chronic stress has been linked to more rapid onset and
progression of chronic illnesses and bodily wear and tear
(which accelerates aging)
Violence can influence health through its impact on
social and economic conditions
Violence can lead to widespread feelings of fear, distrust and
isolation
Violence can act as an obstacle to investments in health-
promoting community resources and opportunities
(supermarkets, jobs, parks)
(RWJ, 2011)
36. NEIGHBORHOOD CHARACTERISTICS
Extremely disadvantaged neighborhoods are characterized by a high
degree of social isolation from mainstream society
Most profound effects of living conditions may be delayed
consequences that unfold over a lifetime
Higher vacancy rates and greater prevalence of renters produce
significantly higher levels of property crime
Many studies have found relationships between neighborhood
disadvantage and health, even after considering individual
characteristics (behavior, income, etc.)
Distressed homes and neighborhoods can induce disease
(lead, allergens, pollution)
Shortage of health care providers, especially primary care
(Krivo & Peterson, 1993; Woolf & Braverman, 2011)
37. HOMICIDE
Higher levels of relative and
absolute deprivation are
associated with higher levels of
homicide
Black-White segregation leads to
higher rates of Black killing
(stranger and acquaintance
homicides)
Social isolation may act as the
mechanism
(Peterson & Krivo, 1993)
39. SEXUALLY TRANSMITTED INFECTIONS
Social determinants create the epidemiological context for
individual behaviors and STI transmission:
SES is one of the most important determinants of sexual
health
High unemployment rates, low mean income and low
education levels are associated with higher STI rates
Disparities in incarceration rates and high mortality for Black
males have lead to disproportionate sex ratios in some
communities (more women than men)
(Hogben and Leichter, 2008; Thomas, Torrone, et al., 2009)
40. STIS AND HIV
CDC identified higher HIV prevalence among
heterosexual individuals who had previously
received an STI diagnosis (4.0%) vs. those who did
not (1.7%)
Transmission and acquisition of HIV may be
increased up to 10 times by the presence of other
sexually transmitted infections
(CDC MMWR 8/12/2011, Logan, Cole & Leukefield, 2002)
44. NATIONAL INCIDENCE DATA
Estimated 48,100 HIV infections in 2009 in adults
and adolescents (95% CI, 42,200 – 54,000)
Estimated incidence 19.0 infections per 100,000
population
44% among blacks, 20% Latinos
61% among MSM, 27% heterosexual
39% among 13-29 year olds
(AACO, 2011)
45. HIV IN PHILADELPHIA
25,563 people are living with HIV/AIDS in the Philadelphia 9
county region, almost 75% of those live in Philly
Estimated another 5,000 HIV+ people are not aware of HIV+
status
Philly’s HIV incidence rates are 4 times national average
It is estimated that 2% of African Americans in Philly are HIV+
46. 2009 ESTIMATE OF HIV INCIDENCE -
PHILADELPHIA
Local estimate of 941 new HIV infections in 2009 in
adults and adolescents (95% CI, 659 – 1,222)
Case rate of 76.8 new HIV infections per 100,000
population
4 times the national rate
90% increase in incidence among youth, 13-24 between
2006 to 2009
Driven by increases in young, black, MSM
47. LOCAL INCIDENCE ESTIMATE - RACE
2009 HIV Diagnoses 2009 HIV Incidence
N=913 N=941
38% 37%
62% 63%
Black Non-Black
Black Non-Black
48. LOCAL INCIDENCE ESTIMATE - AGE
2009 HIV Diagnoses 2009 HIV Incidence
N=913 N=941
17%
27% 25%
30%
48% 53%
13-24 25-44 45+ 13-24 25-44 45+
49. LOCAL INCIDENCE ESTIMATE - MODE
2009 HIV Diagnoses 2009 HIV Incidence
N=913 N=941
36% 39%
47%
50%
14% 14%
MSM IDU Hetero MSM IDU Hetero
50. Mistrust of
Health
Care
System
Social
Inequality
Historic and Modern
Inequality
Increased
Risk of HIV
and STD
Drug
and
Alcoho
l
Abuse Unprotected
Sex
Unsafe/
Unstable Concurrent
Incarceration
Neighborhoods
Partnerships
(Advocates for Youth, 2008)
51. NEIGHBORHOOD CHARACTERISTICS AND HIV
Philadelphia neighborhoods with high rates of HIV
(GENERALLY) have these characteristics:
Low socio-economic status
High concentration of Black/African American residents
High death rates due to homicide, AIDS, septicemia or
other illness
High birth risk
High neighborhood instability
High crime rates of multiple types
(PHMC, 2011)
52. INCOME AND HIV
Material poverty is associated with an increase in
risk behaviors
CDC found HIV prevalence associated with
socioeconomic status:
Prevalence higher among those :
With less than high school education* (2.8%)
Incomes at or below poverty* (2.3%)
Unemployed *(2.6%)
Homeless (3.1%)
*statistically significant differences
(CDC MMWR 8/12/2011)
53. Northeast
Fairmont Airport
Park
La Salle
Pennypack
Clark Park Park
Cobbs
Creek
Park
Phila Int.
Airport
54. BLACK POPULATION
19116
19116
19154
19154
19115
19115
19118
19118 19150
19150
19114
19114
19111
19111 19152
19152
19138
19138 19126
19126
19119
19119
19128
19128
19144
19144
m
n 19141
19141
19120
19120
19149
19149
19136
19136
19127
19127
19124 19135
19135
19124
19129
19129 19140
19140
19132
19132 19137
19137
19133
19133
19131
19131 19134
19134
19121
19121
19151
19151 19122
19122 19125
19125
19130
19130
19139
19139 19123
19123
19104 Legend
19104 19102
19102
19143
m
n
19103 19107
19103 19107
19106
19106 m
n La Salle, City Hall
19143 Airport
19146
19146
19147
19147 Runway
FCC
Parks
19142
19142 Rivers and Streams
19145
19145 tracts
19148
19148 BLACK POP %
0.07% - 4.44%
4.45% - 12.75%
12.76% - 32.4%
19112
19112
19153
19153 32.41% - 69.17%
69.18% - 94.44%
94.45% - 98.65%
Zip Code Boundaries
19113
19113
0 0.40.8 1.6 Miles
55. HISPANIC POPULATION
19116
19116
19154
19154
19115
19115
19118
19118 19150
19150
19114
19114
19111
19111 19152
19152
19138
19138 19126
19126
19119
19119
19128
19128
19144
19144
m
n 19141
19141
19120
19120
19149
19149
19136
19136
19127
19127
19124 19135
19135
19124
19129
19129 19140
19140
19132
19132 19137
19137
19133
19133
19131
19131 19134
19134
19121
19121
19151
19151 19122
19122 19125
19125
19130
19130
19139
19139 19123
19123
19104 Legend
19104 19102
19102
19143
m
n
19103 19107
19103 19107
19106
19106 m
n La Salle, City Hall
19143 Airport
19146
19146
19147
19147 Runway
FCC
Parks
19142
19142 Rivers and Streams
19145
19145 tracts
19148
19148 HISPANIC POP %
0.26% - 1.24%
1.25% - 1.88%
1.89% - 2.75%
19112
19112
19153
19153 2.76% - 4.22%
4.23% - 10.01%
10.02% - 88.49%
Zip Code Boundaries
19113
19113
0 0.40.8 1.6 Miles
56. WHITE POPULATION
19116
19116
19154
19154
19115
19115
19118
19118 19150
19150
19114
19114
19111
19111 19152
19152
19138
19138 19126
19126
19119
19119
19128
19128
19144
19144
m
n 19141
19141
19120
19120
19149
19149
19136
19136
19127
19127
19124 19135
19135
19124
19129
19129 19140
19140
19132
19132 19137
19137
19133
19133
19131
19131 19134
19134
19121
19121
19151
19151 19122
19122 19125
19125
19130
19130
19139
19139 19123
19123
19104 Legend
19104 19102
19102
19143
m
n
19103 19107
19103 19107
19106
19106 m
n La Salle, City Hall
19143 Airport
19146
19146
19147
19147 Runway
FCC
Parks
19142
19142 Rivers and Streams
19145
19145 tracts
19148
19148 WHITE / POP2000
0.28% - 2.41%
2.42% - 16.5%
16.51% - 45.3%
19112
19112
19153
19153 45.31% - 73.6%
73.61% - 90.16%
90.17% - 100%
Zip Code Boundaries
19113
19113
0 0.40.8 1.6 Miles
62. L & I PENDING DEMO, 2005
19116
19116
19154
19154
19115
19115
19118
19118 19150
19150
19114
19114
19111
19111 19152
19152
19138
19138 19126
19126
19119
19119
19128
19128
19144
19144
m
n 19141
19141
19120
19120
19149
19149
19136
19136
19127
19127
19124 19135
19135
19124
19129
19129 19140
19140
19132
19132 19137
19137
19133
19133
19131
19131 19134
19134
19121
19121
19151
19151 19122
19122 19125
19125
19130
19130
19139
19139 19123
19123
19104
19104 Legend
19102
19102
19143
m
n
19103 19107
19103 19107
19106
19106 m
n La Salle, City Hall
19143 Airport
19146
19146
19147
19147 Runway
FCC
Parks
19142
19142 Zip Code Boundaries
19145
19145 Rivers and Streams
19148
19148 tracts
.LIPENDDEMO05
0
1-4
19112
19112
19153
19153 5 - 10
11 - 20
21 - 36
37 - 128
19113
19113
0 0.40.8 1.6 Miles
63. THEFTS, 2011
19116
19116
19154
19154
19115
19115
19118
19118 19150
19150
19114
19114
19111
19111 19152
19152
19138
19138 19126
19126
19119
19119
19128
19128
19144
19144
m
n 19141
19141
19120
19120
19149
19149
19136
19136
19127
19127
19124 19135
19135
19124
19129
19129 19140
19140
19132
19132 19137
19137
19133
19133
19131
19131 19134
19134
19121
19121
19151
19151 19122
19122 19125
19125
19130
19130
19139
19139 19123
19123
19104
19104 19102
19102
19143
m
n
19103 19107
19103 19107
19106
19106
19143
19146
19146
19147
19147 Legend
Thefts
19142
19142
19145
19145 19148
19148
m
n La Salle, City Hall
Airport
Runway
19112
19112
19153
19153 FCC
Parks
Rivers and Streams
19113
19113
Zip Code Boundaries
0 0.40.8 1.6 Miles
Notes de l'éditeur
Concurrent relationships provide for different needs. Main partners offer emotional support and companionship while non-main partners may offer financial, housing or other supports.Among low income African Americans, concurrency is perceived as the norm.Lack of trust in partners, main and non-main also influenced concurrencyTrust also impacts condom use. Condoms more likely to be used with non-main partners.Lack of trust in community, affect marital decisions and concurrent partnerships. Lack of trust is related to lack of social capital in the community. High crime rates, low marriage rates and high poverty rates are associated with low levels of neighborhood social capital, low socioeconinomic status and poor health outcomes.Substance use
Other recent research : Galea, Tracy, Hoggart, DiMaggio, Karpai in APHA Journal 8/2011Estimated that 245,000 deaths in the US in 2000 were attributable to low education 176,000 to racial segregation 162,000 low social support 133,000 individual level poverty 119,000 income inequality 39,000 to area-level povertyArea-level poverty RR 1.22 (CI 1.17, 1.28)Income inequality RR 1.17 (CI 1.06, 1.29)Racial segregation RR 1.59 (CI 1.31, 1.94)
Poverty is not a social driver, per se. It is the context in which people are poor that can lead to relational patterns resulting in forms of sexual networking that can spread HIV Earlier onset of sexual activity occasional transactional sex
In the 40 states and 5 U.S. dependent areas with confidential name-based HIV infection reporting since at least January 2006, the estimated rate of diagnoses of HIV infection among adults and adolescents was 21.1 per 100,000 population in 2009. The rate for adults and adolescents diagnosed with HIV infection ranged from zero per 100,000 in American Samoa and the Northern Mariana Islands to 40.6 per 100,000 in Georgia.The following 40 states have had laws or regulations requiring confidential name-based HIV infection reporting since at least January 2006: Alabama, Alaska, Arizona, Arkansas, Colorado, Connecticut, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Michigan, Minnesota, Mississippi, Missouri, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, West Virginia, Wisconsin, and Wyoming. The 5 U.S. dependent areas include American Samoa, Guam, the Northern Mariana Islands, Puerto Rico and the U.S. Virgin Islands. Data include persons with a diagnosis of HIV infection regardless of stage of disease at diagnosis. All displayed data have been estimated. Estimated numbers resulted from statistical adjustment that accounted for reporting delays, but not for incomplete reporting.
Estimated rates (per 100,000 population) of adults and adolescents living with a diagnosis of HIV infection at the end of 2008 in the 40 states and 5 U.S. dependent areas with confidential name-based HIV infection reporting since at least January 2006 are shown in this slide. Areas with the highest estimated rates of persons living with a diagnosis of HIV infection at the end of 2008 were New York (826.7), the U.S. Virgin Islands (663.7), Florida (586.2), Puerto Rico (575.4), New Jersey (513.2), Georgia (450.0) and Louisiana (444.3). The following 40 states have had laws or regulations requiring confidential name-based HIV infection reporting since at least January 2006: Alabama, Alaska, Arizona, Arkansas, Colorado, Connecticut, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Michigan, Minnesota, Mississippi, Missouri, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, West Virginia, Wisconsin, and Wyoming. The 5 U.S. dependent areas include American Samoa, Guam, the Northern Mariana Islands, Puerto Rico and the U.S. Virgin Islands. Data include persons with a diagnosis of HIV infection regardless of stage of disease at diagnosis. All displayed data have been estimated. Estimated numbers resulted from statistical adjustment that accounted for reporting delays, but not for incomplete reporting. Persons living with a diagnosis of HIV infection are classified as adult or adolescent based on age at end of 2008.
Black population total 661, 839 = a little over 13,000
In this case incidence is an estimate. It represents the number of people the epidemiologist for the city of Philadelphia believes to be infected. In the best case scenario you would want the number of people diagnosed to be greater than the number of people believed to be infected, that way you would stand a better chance of reducing the number of new infections.
Social drivers are understood not as unilateral variables that can be studied adequately in terms of causal, one-to-one relationships between any of them and HIV infection outcomes….they are interactive phenomena reflective of social and cultural processes, institutional practices, and sets of arrangements that facilitate HIV transmission or its prevention.Social drivers are complex, fluid, non-linear,and contextual, and they interact dynamically with biological, psychological, behavioral and other social factors
The CDC reported August of 2011 in the mmwr that there is an association between poverty and risk behaviors.
661, 839 42.7%
11.15% or 172,483 Asians are 96,405 6.23% Nat amer a little less than 7,000
40.47 or 626,211
There were 68,550 or 11.4 total female headed households with their own children present.Total households 599,736
574,413 total households for whom income was determined.16.8% <$10,0008.4 10 to 14,99913.8 15 to 24,99916.2 50 to 74,999Median household income $34,40027.9% social security10.7% SSI22.1 some public assistance including food stamps39.7 public health insuranceEmployed –no health ins. 17%Unemployed –no health ins 46.1%21.3% of all families below poverty level31.3 Poverty children under 18, 27% with children under 5