DATOS INICIALES DE OPERACIÓN SISTEMA DE 500 kV EN EL PRE EVENTO EN

This study is not without limitations. With respect to collecting primary data using survey methodology such as convenience sampling and self-identification of race limited how representative the sample was of all Blacks in Charleston MSA. Many of the respondents were highly educated, which suggests they may have been more

knowledgeable about the risk factors associated with. According to the American Community Survey, educational attainment estimates from 2006 to 2010 among Black adults (males and females age 25 or old) in the Charleston MSA was primarily at the high school level (U.S. Census Bureau, 2014f). Hence, the sample having more education may have affected the respondents health behaviors, especially those related to screening

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recommendations. Using self-report data has its challenges, mainly introducing nature to biases, such as social desirability and recall bias. Some respondents may have

overestimated their health behaviors or inaccurately reported past behaviors due to recall or social desirability bias. To prevent recall bias, a timeframe was incorporated into items cancer risk factors, but recalling information accurately can be a challenge especially since the majority of respondents were over age 45. A cross-sectional study design was used for the survey, but respondents were not required to answer all questions. Hence, this study was subject to non-response error which may have influenced the

generalizability or the representativeness of the sample (Yoon & Horne, 2004). Using a cross-sectional study design limits the ability to determine causal inference (i.e. determine whether respondents’ perceived cancer risk prompted them to respond to their health and thus behavior according to recommended guidelines or if respondents’ behaved according to their environment which in turn prompted them to engage in risky or health-protective behaviors) (Levin, 2006). Despite having limitations in the study design, a preliminary snapshot of health behaviors associated with risk factors for cancer was observed in a population with excess cancer burden and environmental exposures. Since this study was exploratory in nature, no statistical interactions were conducted. The primary focus was on determining the relationships between factors, which were tested and discussed. Although conducting interactions between variables was beyond the scope of this study, performing such an analysis in the future has implications for future research. For this study, secondary data analysis was used to explore relationships between cancer and environmental disparities. A disadvantage to using secondary data is that their inabilities to fulfill every objective data were retrieved to assess (Greenstein, 2012). For this work,

there was data pertinent to the dissertation that may not have been collected, may be missing, and/or may be incomplete because it was beyond the scope of the original study. Interruptions in the data such as those previously mentioned may lead to an

underestimation or overestimation of the correlation between measures, thus biasing the results. Census data, in general, has its own limitations. Census data collection varies by data collected. For example, the Census is collected decennially and some housing (i.e. American Housing Survey) is collected biennially. In addition, American Community Survey data are collected annually; however, single-year and multi-year estimates are not produced for all population sizes, which can be a limitation (U.S. Census Bureau, 2009). Some statistics used in the Census are based on complete enumerations versus samples of the population. NATA data limitations vary by year (U.S. EPA, 2010a; U.S. EPA, 2010b; U.S. EPA, 2010c; U.S. EPA, 2010d). A few limitations that posed a threat to this study include: default assumptions used to estimate risks, potential gaps in data; risk estimates only reflect outdoor exposures, and the use of aerial data rather than location- specific data. A major limitation associated with the use of SCCCR cancer incidence data is the accessibility and availability of the data including limitations in representing actual rates in areas with small numbers.

Despite its limitations, this study has several strengthens. First, the study utilized an interdisciplinary approach to better understand a significant public health concern in Charleston MSA as well as nationally. Using an interdisciplinary approach drew upon theoretical concepts, methodological techniques, and diverse disciplines (e.g., health behavior, geography, and epidemiology) to demonstrate where disparities exist and show that more policies, and out-of-the-box thinking is needed. In addition, study findings can

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serve to inform dialogue on eradicating cancer and environmental health disparities using comprehensive approach. Another strengthen is how this study expands upon past and current literature on cancer and environmental health risk perceptions. Most of the literature on environmental health risk is outdated and does not explore overlapping disparities in relation to health behaviors and from the perspective of a “high risk” group as this study did. Cancer risk perceptions literature, on the other hand, is update but lacks there has been little to no discussion of overlapping risk and disparities. Also, a major strengthen to this study is its ability to expand the literature surrounding Blacks’ perceiving they are at lower risk of developing cancer. Other studies have inferred that lower perceptions in this group were due to a lack of knowledge of family history of disease (Orom et al., 2010). However, in this study, respondents provided several

explanations for their cancer risk perceptions. The ultimate strength of this study is that it  

is the only one to date that has statistically analyzed items from the PEW survey. Findings from this study can inform the development of cancer prevention and

environmental health disparities interventions. Informing interventions will help public health professionals identify vulnerable areas where perceptions of cancer risk are low, health disparities exist and persistent and how geographic location places a role in disparities.