Psychological Health Outcomes Data

No discussion of data on health outcomes related to the environment is complete without consideration of data on psychological health outcomes.  For purposes of this report, psychological health does not include neurological disorders such as autism and learning disabilities, i.e., those which have a largely physiological basis, and are considered separately above.  While neurological conditions are included in some the information sources on psychological health, our focus here is upon data outcomes with an emotional or perceptual basis linked to one’s environment.  This may include depression, stress, anxiety, and outcomes and behaviors linked to one’s state of psychological well-being.  However, one should not discount that fact that psychological factors such as stress are, in turn, linked to physiological conditions such as suppressed immune response[352] and heart disease.[353]

Environmental factors can influence mental health in numerous ways.  For example, the features of a person’s perception of their environment may affect their attitudes and behaviors.  As discussed later under the Built Environment section, several studies by Kuo et al. illustrate that the presence of trees and green spaces can influence children’s school performance, crime rates, and violent behavior.[354]  Additionally, environmental factors may stimulate behaviors beneficial to mental health either directly or indirectly—for example, a nearby trail may encourage a person to engage in physical activity, which may in turn lessen depression and stress levels.

As with physical health, several different types of outcome data for mental health exist.  Although the aggregate levels at which many of them are readily and publicly available are not geographically detailed enough for serious environmental health research, we list a few of them below.  This will at least provide some starting points for obtaining more detailed data if necessary. 

Mental Health Service Utilization Data 

These data sets may be very fragmented due to different funding streams and administrative oversight for services.  For example, public agency datasets will exclude individuals whose treatment is not partially or entirely covered by public funds, e.g., those pay out-of-pocket for private treatment.  Laws originally set up to protect individual privacy can make it difficult for bureaus overseeing different types of services to the same individual to share information with one another.[355]  Also, many individuals from low-income backgrounds have poorer access to care, either due to lack of health insurance or other coverage, difficulty obtaining transportation access to health care providers, a lack of time to spend waiting in exceptionally crowded facilities (e.g., hospital waiting rooms in underserved areas), schedule constraints due to job and family (e.g., a single mother working two jobs that offer little or no sick/vacation leave), or lack of education regarding the importance of preventive treatment.  Thus, their mental health conditions may never even show up in service utilization data.

The Pennsylvania Health Care Cost Containment Council (PHC4) dataset described above contains information on individuals involuntarily admitted for emergency treatment “necessary to protect the life or health, or both, of the individual or to control behavior by the individual which is likely to result in physical injury to others.” [356], [357]  The Allegheny County Department of Human Services (DHS) maintains various datasets internally, but privacy and confidentially concerns must be addressed before such data can be shared more openly.  Additionally, limited treatment data, aggregated for large areas, are available online.  Within the U.S. Department of Health and Human Services, the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Office of Applied Studies website provides data including state and county-level statistics on substance abuse treatment admissions, and metropolitan area statistics for drug-related emergency room visits and drug-related deaths.[358]   

Data on Educational Test Performance and School Attendance

A child’s environment may impact such psychological health factors as their ability to pay attention in school and self-discipline, which in turn may be reflected in their performance on standardized educational tests[359] and behaviors such as school attendance rate.  School-district level data for the entire state is available through Standard and Poor’s School Evaluation website.[360]  These include data on standardized test passing rates, attendance rates, dropout rates and disciplinary sanctions, along with various other school district characteristics (e.g., spending per student and percent economically disadvantaged) that also impact these data—and must thus be controlled for in any statistical study.  Some of these data are also available through the Pennsylvania Department of Education’s website,[361] and accompanying school-level demographics can be obtained through the Pittsburgh Public School Data Atlas at the University of Pittsburgh’s Visual Information Systems Center.[362] 

Child Developmental Disabilities: School Special Education Data

Section 618 of the Individuals with Disabilities Education Act (IDEA) requires school districts to annually report data on enrollment numbers for children receiving special education services to the U.S. Department of Education.  These include data on children ages birth through 2, and 3 though 21+.[363]   Although it includes primarily neurological disorders, which are addressed above, it also includes some psychological conditions.  The Pennsylvania Department of Education’s “Penn Data Special Education Reporting System” reports include numbers of enrolled children with conditions including mental retardation, hearing impairments, speech or language impairments, visual impairments, emotional disturbance, orthopedic impairments, specific learning disabilities, deaf-blindness, multiple disabilities, autism, and developmental delay.[364]  These reports include data summarized for each of Pennsylvania’s 29 intermediate unit regions, as well as school districts within each region and charter schools, for school years 1990-1991 through 2003-2003.  The U.S. Department of Education’s website also has state-level reports with much of this information.[365]

Crime and Violent Behavior

As discussed later under the Built Environment section, one’s environment may elicit psychological and behavioral responses—i.e., lack of exposure to green space may be linked to violence and criminal behavior.[366], [367]   In addition to the Pittsburgh Police Department reports data listed in the Built Environment section, some data are more easily accessible but on a larger geographic scale.  The FBI Uniform Crime Reports (UCR) include arrests and reported offenses collected and reported by local police departments.  Data are broken out by different categories of crime, including violent versus non-violent offenses.  One should keep in mind that these do not reflect data such as 911 calls where police were dispatched, but no report was filed.  Some crime information at a sub-city level, including data on serious assaults and homicides for Pittsburgh, is available at the website of the National Consortium on Violence Research (NCOVR),[368] headquarted locally at Carnegie Mellon University’s Heinz School of Public Policy and Management.  As for school violence, the State Department of Education’s School Violence and Weapons Possession Reporting System includes county-level data for the 1999-2000 through 2002-2003 school years.[369]  Data on reported and investigated child abuse and neglect, another type of violent behavior, is maintained by the Pennsylvania Department of Welfare, Office of Children, Youth and Families.[370]  Death records, mentioned earlier in the Health Outcomes Section, include causes of death such as homicide.[371]  For most types of crime and violent behavior data, however, keep in mind that a great deal may never even be reported.

Qualitative Survey Information 

This may include self-reported perception of psychological well-being, behaviors associated with psychological well-being, and utilization of mental health services (e.g., “How often do you visit a counselor for depression?”).  Due to the cost and effort of gathering such data, they are generally for a small proportion of people over a large geographic area, or a somewhat larger proportion of people within a very limited geographic area.  The Behavioral Risk Factor Surveillance System (BRFSS) mentioned earlier, which included an expanded example for Pittsburgh,[372] includes data on self-reported alcohol use.  The National Institute of Mental Health’s Epidemiologic Catchment Area (ECA) Program surveyed more than 20,000 respondents across five cities in the early 1980s.  Its goals included gathering data on the prevalence and incidence of 17 major mental disorders.[373], [374]  In the early 1990s, the National Comorbidity Survey (NCS) sought to gather data on mental health disorders using a nationally representative sample.  These respondents were interviewed again in 2001-2002 for the NCS-2, and 10,000 new respondents were added through the NCS Replication Survey (NCS-R).[375], [376]  These studies may serve as models for gathering more comprehensive data in the Pittsburgh region, with sample sizes large enough for analysis alongside small-area environmental factors. 

General Psychological Health Data Limitations

Psychological health data have a few general limitations.  One is that a particular psychological illness or condition may or may not be reflective of an individual’s more global mental health or state of psychological well-being, or their perceived quality of life.[377]  Frequently, we have only a small piece of the overall picture.  Additionally, a person’s current condition may have been shaped by previous experiences in a completely different environment.  A child attending school in one district may have been born and raised in a community with a completely different mix of environmental factors.  Furthermore, whereas many physiological conditions can be represented by data on a simple binary basis (e.g., either a person has had cancer or they have not), many psychological conditions may be better represented on a continuous scale (e.g., sometimes sad, always sad) that may not be accurately represented in a data set.  Having a diagnosed condition such as clinical depression from the DSM, or Diagnostic and Statistical Manual of Mental Disorders, would be the closest approximation of such binary data.  Even so, mental disorders are difficult to quantify because their diagnosis often involves a certain symptom “threshold,” i.e., the individual must exhibit a certain number of symptoms over a certain period of time.[378]  Also, diagnoses as defined in the Diagnostic and Statistical Manual of Mental Disorders (DSM) change with each revision.

Finally, little data exist on some pertinent topics.  For example, some evidence suggests that feelings of personal inadequacy are linked to materialistic behavior.[379]  This might include, for example, purchasing a larger house and larger automobile in an attempt to compensate for feelings of inadequacy.  Such materialistic behavior, in turn, may further deteriorate the environment and impact health, as described in the Consumer Demands and Polluting Activities section and elsewhere.[380]  While there do not currently appear to be any comprehensive data sources on insecurity and feelings of self-worth, surveys collecting such data could be informative to the environmental health community.