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How individual and neighborhood characteristics relate to health topic awareness and information seeking

机译：个人和邻里特征如何与健康主题意识和信息寻求有关

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Structural determinants of health like neighborhood are often overlooked in the context of understanding public awareness of health topics and health information seeking behaviors. Seeking health information is particularly relevant given that some communities have higher prevalence of disease than others. Using the Structural Influence Model of Health Communication (SIMHC), this paper examines how both individual and neighborhood level characteristics contribute to health communication outcomes such as being aware of health topics like cancer, obesity, and HIV, and whether or not individual seeking health-related information or coming across information in the course of their general media use. Respondents to the Southeastern Pennsylvania Household Health Survey (SEPa HHS), a county-stratified random sample of adults ages 18-75 years old, who completed the survey in 2015, were recontacted for participation in 2017. Over one-thousand respondents (n=1,005) completed the survey, and the final sample size for this analysis was 887. Individual level correlates included demographic factors and relevant lifestyle behaviors (e.g., smoking); neighborhood level variables- determined by ZIP Code- included such socioeconomic status (SES) measures as percent unemployed, percent with a high school education, and percent living in poverty. Multilevel modeling was used to determine whether there were random effects on the health communication outcomes of interest. Analyses showed our outcomes of interest did not vary across neighborhoods, whether they were treated as random or fixed effects. Different characterizations of neighborhood (e.g., census block group) and different indicators of neighborhood media environments may be more likely to demonstrate macro level effects on health communication outcomes.
机译：在理解公众对健康主题和健康信息寻求行为的情况下，邻居的健康状况的结构决定因素通常被忽视。鉴于某些社区的疾病普遍性比其他社区患病率较高，寻求健康信息尤为重要。使用健康通信结构影响模型（SIMHC），本文研究了个人和邻里级别特征如何促进健康通信结果，例如了解癌症，肥胖和艾滋病毒等健康主题，以及是否寻求健康的个人 - 相关信息或在普通媒体使用过程中跨越信息。宾夕法尼亚州东南部家庭健康调查（SEPA HHS），18-75岁的县分层随机样本于2015年完成调查，于2017年再接受参加。超过一千个受访者（n = 1,005）完成了调查，此分析的最终样本大小为887.个人水平相关包括人口因子和相关的生活方式行为（例如，吸烟）;由邮政编码决定的邻里级别变量 - 包括失业率百分比，高中教育的百分比和贫困百分比的衡量标准。多级建模用于确定对健康通信结果是否存在随机效应。分析表明我们的兴趣结果不会因围绕社区而异，无论它们是否被视为随机或固定效果。社区（例如，人口普查块组）的不同特征和邻域媒体环境的不同指标可能更有可能展示对健康通信结果的宏观级别影响。

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