Measuring Quality of Life in Communities Surrounding Airports (2020)

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13 Quality of Life Methodology By understanding the factors that positively or negatively affect QOL, airports can gain insight into how their operations and decisions affect surrounding communities. This project provides a framework to help airports and communities measure and track QOL for a baseline year and over time. The Quality of Life Assessment Methodology developed for this guidebook was based on existing QOL studies and on a similar tool developed by Eastern Research Group (ERG) and EPA for evaluating resilience of communities to the impacts of climate change, as developed by Blue, Hiremath, Gillette, and Julius (2017). The EPA tool is known as the Multisector Evaluation Tool for identifying Resilience Opportunities, or METRO. Some factors affecting QOL in a community—such as economic health, air quality, and water quality—can be measured quantitatively through publicly available datasets. Other factors are not reflected in this type of available data. These are best addressed by asking community members for their input, including the factor’s relative importance and how it currently affects their QOL. As described in Section 1.5, the research team selected a mixed­methods approach to assessing QOL, incorporating hard data (when available) and qualitative information collected from community members to address QOL comprehensively. A QOL assessment approach that integrates both quantitative and qualitative information increases understanding of the broad influence that airports have on local communities and can eventually support airport leadership in making decisions that are beneficial to local QOL. Perhaps even more importantly, involvement in assessing the QOL of the local community demonstrates to communities that the airport is aware of and considerate of its effects on its neighbors. This can help foster improved relationships between airports and communities. 2.1 Quantitative and Qualitative Indicators The list of 100 indicators for evaluating QOL is a mix of quantitative and qualitative indicators (Table 1). For the quantitative indicators, existing data sets are used to score QOL (suggested data sources for each quantitative indicator are provided in the Indicator Thresholds and Quan­ titative Data Sources, found at www.trb.org by searching for “ACRP Research Report 221”). For the qualitative indicators, the assessment methodology includes the Quality of Life Assessment Survey Tool, also found at www.trb.org. The survey contains a question for each qualitative indicator. Survey respondents must answer multiple choice questions, and the answer choice corresponds to a QOL score from 1 to 4 (low to high QOL represented by each indicator); therefore, providing a rough quantitative score for the qualitative information collected. In addition, survey respondents are asked to rate how important each indicator is to their overall QOL. This “importance score” is then used to weight the importance of that indicator to the overall assessment, as discussed further in Section 2.4. C H A P T E R 2

14 Measuring Quality of Life in Communities Surrounding Airports Indicator ID Type GENERAL 01 Qualitative Overall quality of life Indicator ID Type ENVIRONMENTAL EN1 Qualitative Satisfaction with local air and water quality EN2 Qualitative Quality of parks and natural spaces EN3 Qualitative Frequency of visiting parks and natural spaces EN4 Qualitative Local aesthetics EN5 Qualitative Water quantity EN6 Qualitative Satisfaction with housing EN7 Qualitative Convenience to amenities EN8 Qualitative Light pollution EN9 Qualitative Satisfaction with the environmental stewardship of nearest airport EN10 Qualitative Intensity of aircraft noise annoyance EN11 Qualitative Environmental justice EN12 Quantitative Outdoor air quality EN13 Quantitative Amount of public parklands EN14 Quantitative Amount of protected areas Indicator ID Type HEALTH H1 Qualitative Satisfaction with health H2 Qualitative Physical health status H3 Qualitative Mental health status H4 Qualitative Impact of health on ability to perform daily activities H5 Qualitative Exercise frequency H6 Qualitative Diet H7 Qualitative Level of stress H8 Qualitative Meaning and purpose in life H9 Qualitative Self-esteem H10 Qualitative Hope and optimism H11 Qualitative Recent happiness H12 Qualitative Screen use H13 Qualitative Access to health care H14 Qualitative Access to recreation facilities (indoor or outdoor) H15 Qualitative Ability to obtain fruits and vegetables H16 Qualitative Ability to concentrate (in relation to noise-related disturbances) H17 Qualitative Sleep disturbances H18 Qualitative Indoor heating and cooling comfort H19 Quantitative Workplace safety H20 Quantitative Asthma prevalence H21 Quantitative Obesity prevalence H22 Quantitative Percentage of population with disabilities Table 1. Quality of life indicators.

Quality of Life Methodology 15 Indicator ID Type ECONOMIC E1 Qualitative Household disposable income E2 Qualitative Ability of household income to meet the basic needs of the household E3 Qualitative Ability to afford unexpected expenses E4 Qualitative Comparative income E5 Qualitative Access to financial resources E6 Qualitative Housing affordability E7 Qualitative Health care affordability E8 Qualitative Access to affordable child care E9 Qualitative Job satisfaction E10 Qualitative Job security E11 Qualitative Time at work E12 Qualitative Work–leisure balance E13 Qualitative Opportunities for advancement E14 Qualitative Opportunities for acquiring new information and skills E15 Quantitative Household income E16 Quantitative Job opportunities E17 Quantitative Economic growth E18 Quantitative Unemployment rate E19 Quantitative Percentage of people living below poverty line E20 Quantitative Housing affordability E21 Quantitative Homelessness E22 Quantitative Gender gap E23 Quantitative Percentage of high school graduates Indicator ID Type TRANSPORTATION T1 Qualitative Traffic congestion T2 Qualitative Access to transportation T3 Qualitative Satisfaction with public transportation T4 Qualitative Transportation system redundancy T5 Qualitative Maintenance of transportation infrastructure T6 Qualitative Bicycle and pedestrian routes T7 Qualitative Access to transportation by vulnerable populations T8 Qualitative Satisfaction with nearest airport T9 Quantitative Traffic congestion T10 Quantitative Active transportation for commuting T11 Quantitative Public transportation for commuting T12 Quantitative Vehicle safety S1 Qualitative Feeling of belonging to community Indicator ID Type SOCIAL RELATIONSHIPS S2 Qualitative Social connectedness S3 Qualitative Connection with neighbors S4 Qualitative Satisfaction with community events S5 Qualitative Time off work (e.g., weekends and vacations) S6 Qualitative Volunteerism S7 Qualitative Acts of service or assistance S8 Qualitative Religious or spiritual engagement S9 Qualitative Feeling that most people are trustworthy S10 Qualitative Resolution of conflicts with others S11 Qualitative Experience of discrimination Table 1. (Continued). (continued on next page)

16 Measuring Quality of Life in Communities Surrounding Airports 2.2 Selection of Indicators Although airport personnel are the intended audience for this guidebook and the accom­ panying tools, the Quality of Life Assessment Methodology is robust and flexible enough that it can also be implemented by community organizations—such as chambers of commerce or tourism agencies—either to support the airport’s interest in the assessment or for their own assessment purposes. Each of the 100 indicators in the Quality of Life Assessment Methodology has been slotted into one of the six categories introduced in Section 1.4 and in Figure 3. The quantitative indicators represent a minority of the indicators selected because many QOL components are not reflected in data sets that would generally be available in communities surrounding airports (or any community, for that matter). As a result, most of the indicators are qualitative. The qualitative indicators are framed as questions in the survey tool (which is a key element of the methodology). If the airport chooses to administer the survey to community residents, there is some subjectivity expected in the answers to be provided during the assessment. The information that community members have about what influences their own QOL is better captured by using a full range of qualitative indicators than by limiting the assessment to information that could be gleaned from the narrower set of relevant quantitative indicators. The Indicator Thresholds and Quantitative Data Sources at www.trb.org and in Table 1 present the full list of quantitative and qualitative indicators included in the Quality of Life Assessment Methodology. Information on how data can be gathered for these indicators is described in Chapter 4. Indicator ID Type LOCAL GOVERNANCE–COMMUNITY SERVICES G1 Qualitative Satisfaction with public services G2 Qualitative Access to local services G3 Qualitative Equitable access to local services G4 Qualitative Quality of public education system G5 Qualitative Community safety G6 Qualitative Emergency notification system(s) G7 Qualitative Waste diversion G8 Qualitative Availability of services for disabled persons G9 Qualitative Community resilience G10 Qualitative Perception that your input matters in government G11 Qualitative Trust in public officials G12 Qualitative Local commitment to long-term planning G13 Qualitative Consideration of vulnerable populations G14 Qualitative Support available to caregivers G15 Quantitative Emergency medical service response time G16 Quantitative Violent crime G17 Quantitative Voter turnout Note: Shaded and italicized indicators represent quantitative indicators, which can be assessed through the collection and analysis of publicly available data (described further in Chapter 3 and in Appendix B: Indicator Thresholds and Quantitative Data Sources, found at www.trb.org by searching for “ACRP Research Report 221”). Table 1. (Continued).

Quality of Life Methodology 17 2.2.1 Supplemental Indicators The Quality of Life Assessment Methodology is designed to provide flexibility to meet the needs of unique airports. Collecting data for all 100 indicators is suggested under the Quality of Life Assessment Methodology (described in Chapter 3) to ensure a comprehensive study of QOL. The methodology allows the list of indicators to be altered by individual airports to best meet their needs when designing and completing the assessment process, allowing for flexibility. The primary set of 100 indicators was developed based on input from subject matter experts, airport personnel, the ACRP project panel (an advisory panel of technical industry experts), and community stakeholders at three partner airports. However, local conditions vary from airport to airport, and the airport or stakeholders may identify the possibility of significant information gaps using only the provided list of indicators. In these cases, the airport can add or substitute some customized, supplemental indicators to make the QOL assessment more locally relevant, as shown in Table 2. The Indicator Thresholds and Quantitative Data Sources tool at www.trb.org includes example supplemental indicators that can be added to the Quality of Life Assessment Survey Tool. They can also be used to replace indicators already in the survey tool, for example, if the data does not exist for a certain quantitative indicator or if an existing indicator is not applicable to a certain airport. Airports are free to develop additional qualitative or quantitative indicators to address specific issues of importance to them or their stakeholders. Too many custom supplemental indicators may jeopardize the ability of a QOL assessment to capture information under the six categories of QOL, as identified by the research team and validated through the research process. Thus, the research team recommends that supplemental indicators be used sparingly unless an airport’s situation diverges significantly from those of Indicator ID Type ENVIRONMENTAL XX Qualitative Access to parks and natural spaces XX Quantitative Drought potential XX Quantitative Watershed quality Indicator ID Type HEALTH XX Qualitative Frequency of moments of extreme happiness XX Qualitative Spirituality or faith (as related to health) Indicator ID Type TRANSPORTATION XX Qualitative Quality of transportation infrastructure XX Qualitative Transparency in airport planning Indicator ID Type LOCAL GOVERNANCE–COMMUNITY SERVICES XX Qualitative Stormwater runoff infrastructure capacity XX Qualitative Condition of existing public infrastructure XX Qualitative Trust in law enforcement XX Qualitative Trust in legal system Note: XX = the indicator ID number assigned by the user. It should begin with an “S” to designate it as “supplemental,” then the letter of the appropriate category, and followed by a number starting with “1”. For example, if an airport develops two supplemental Environmental indicators for its QOL assessment, it would be given the indicator numbers S-EN1 and S-EN2. If the airport also develops one supplemental Health indicator and one supplemental Transportation indicator, it would receive identification numbers S-H1 and S-T1, respectively. Table 2. Example supplemental indicators.

18 Measuring Quality of Life in Communities Surrounding Airports most U.S. airports. The research team also advises that the original list of 100 indicators be used without making any modifications. However, either approach will lead to a valuable assessment of community QOL to inform future decision making and improve understanding between the airport and the surrounding community. 2.3 Indicator Quality of Life Scoring Mechanism Each of the 100 qualitative and quantitative indicators shown in Table 1 can be assigned a score from 1 to 4 representing low to high QOL. Each quantitative indicator is assigned a QOL score based on a set of threshold values (determined based on national data sets and described further in Chapter 4). Each qualitative indicator is assigned a QOL score based on participants’ responses to the survey questions. These scores are used in a QOL assessment to map collected data for each indicator onto the same scale. Indicators that receive a QOL score of 1 are associ­ ated with low QOL for that indicator (in the context of the specific community being evaluated), while a score of 3 or 4 indicates a high QOL for that indicator. 2.3.1 Scoring Quantitative Indicators For each of the quantitative indicators presented in Table 1, publicly available data were combined with findings from the literature to determine three indicator value thresholds repre­ senting points at which the result changes from representing low QOL (an indicator score of 1) to a fair QOL (an indicator score of 2), from fair QOL (an indicator score of 2) to improved QOL (an indicator score of 3), and from improved QOL (an indicator score of 3) to a high QOL (an indicator score equal to 4). The three threshold values defined for each indicator create the upper and lower boundaries used to assign QOL scores of 1, 2, 3, and 4 to data results. As an example, consider a scenario in which data were collected from the U.S. Census Bureau for Indicator E19 (i.e., the percentage of people living below the poverty line). For this indicator, QOL scores would be assigned using the indicator’s unique thresholds as follows: • A QOL score of 1 would be assigned to a community where 20 percent or more of the population lives below the poverty line, • A QOL score of 2 would be assigned to a community where 16 percent to less than 20 percent of the population lives below the poverty line, • A QOL score of 3 would be assigned to a community where 12 percent to less than 16 percent of the population lives below the poverty line, and • A QOL score of 4 would be assigned to a community where less than 12 percent of the population lives below the poverty line. Section 4.1 provides additional instructions for gathering quantitative data and assigning QOL scores. The Indicator Thresholds and Quantitative Data Sources at www.trb.org provides a list of the quantitative indicators, the thresholds, and data sources, along with instructions for obtaining information from the identified data sources. Details on how thresholds were derived are included in Appendix D: Process for Developing Quality of Life Assessment Methodology. 2.3.2 Scoring Qualitative Indicators Qualitative indicators—as listed in Table 1—are represented by a question in the QOL Assessment Survey Tool, including a defined set of four response options. QOL scores ranging from 1 to 4 are assigned to each pre­set response to the questions included in the survey tool. For example, Indicator EN1 (satisfaction with local air and water quality) asks an individual to respond to “How satisfied are you with air and water quality in your community?” by selecting

Quality of Life Methodology 19 one of the following responses: “dissatisfied,” “somewhat dissatisfied,” “somewhat satisfied,” or “satisfied.” In this case, QOL scores would be assigned as follows: • A QOL score of 1 is assigned for a response of “dissatisfied,” • A QOL score of 2 is assigned for a response of “somewhat dissatisfied,” • A QOL score of 3 is assigned for a response of “somewhat satisfied,” and • A QOL score of 4 is assigned for a response of “satisfied.” Additional instructions for how to gather qualitative data and assign QOL scores are provided in Section 4.2, and a complete list of the qualitative indicator questions and responses is included in Appendix A: Quality of Life Assessment Survey Tool. 2.4 Indicator Weighting Mechanism An important part of the Quality of Life Assessment Methodology includes prioritizing which indicators contribute the most to QOL or detract the most from QOL. As noted above, for each of the 100 indicators, the QOL score shows how an individual community member is faring—or, collectively, how the community is faring—with relation to the component repre­ sented by that QOL indicator (e.g., high QOL is represented by a score equal to 4, and a low QOL is represented by a score equal to 1 for the specific indicator). However, the importance of each indicator will likely vary across communities, so it is not advisable to weight each indicator equally in the assessment. Some indicators may be very important to overall QOL, and some indicators may be minor with regard to how they affect overall QOL for an individual (regard­ less of whether the QOL score is high or low for that indicator). For this reason, the methodology uses the calculation of “importance scores” to reflect the degree to which an indicator contributes to overall QOL so that each indicator is not weighted equally. Importance scores vary from 1 to 4. For example, an importance score of 1 represents low importance for an indicator with respect to a respondent’s overall QOL, and a 4 represents high importance. Importance scores for each indicator are captured using the Quality of Life Assessment Survey Tool. For example, the research team anticipates that many participants may rank Indicator H1 (personal satisfaction with health) with an importance score of 4 (high importance), since it is universally applicable and poor health has the ability to affect most aspects of an individual’s life. In contrast, an indicator such as T4 (transportation system redundancy), may receive a lower importance score as it is not universally applicable. Some participants may believe low redundancy in the public transportation system is unlikely to affect their QOL significantly if they have access to a reliable personal vehicle. Other individuals may rank Indicator T4 with a higher importance score if they are dependent on public transpor­ tation for commuting to work or school or if they live in areas where the transportation system is unreliable due to scheduling, weather, or recurring maintenance problems.