| Literature DB >> 27604549 |
Jennifer M Kreslake1, Katherine M Price2, Mona Sarfaty2.
Abstract
BACKGROUND: Individuals with chronic health conditions or low socioeconomic status (SES) are more vulnerable to the health impacts of climate change. Health communication can provide information on the management of these impacts. This study tested, among vulnerable audiences, whether viewing targeted materials increases knowledge about the health impacts of climate change and strength of climate change beliefs, and whether each are associated with stronger intentions to practice recommended behaviors.Entities:
Keywords: Chronic disease management; Climate change; Global warming; Health communication; Health disparities; Health impacts; Health literacy
Mesh:
Year: 2016 PMID: 27604549 PMCID: PMC5015239 DOI: 10.1186/s12889-016-3546-3
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Key design features and content included in study materials
| Details about one health condition affected by climate change |
| • Asthma |
| Human figure icons in conversation (via speech bubbles) about relationship between climate change and health conditions |
| Mechanisms of climate change, explained at 8th-grade readability level or lower |
| • “Carbon pollution makes the world warmer and changes our climate.” |
| Recommended actions |
| • Individual protective or preventive behaviors toward climate change adaptation (“Healthy You”) |
Coding scheme for inductive analysis of in-depth interviews (N = 11)
| Number of mentions | |
|---|---|
| Themes (with associated codes) | |
| Weather is better understood than climate change | |
| Personal experience/anecdotal evidence | 27 |
| Hot weather/heat: immediate concerns | 23 |
| Pollution: disconnected from weather | 6 |
| General understanding of climate change | 1 |
| Weather conditions (not climate change) | 1 |
| Confusion/misinterpretation/unintended consequences | |
| Dietary advice/advice to lose weight (disconnected from environmental impact, food systems or climate change) | 28 |
| Demonstrated gaps in existing knowledge | 27 |
| Confusion about meaning | 16 |
| Poster offers impractical advice | 10 |
| Advice to engage in harmful activity (e.g., advice to engage in walking/biking on poster about heat effects) | 6 |
| Health education strategies | |
| Activating existing knowledge | 18 |
| Intended audience/who should see | 17 |
| Suggested locations/venues to display | 13 |
| Health vulnerabilities | 13 |
| Not enough information provided | 11 |
| Appeal/liking | 8 |
| Recognition of self as audience | 3 |
| Behavioral modeling | 3 |
| Lack of available education on topic(s) | 3 |
| Poor populations | 1 |
| Shock/fear appeals | 1 |
| Attitudes and beliefs about climate change and health | |
| Explains mechanisms of climate change effects on health | 17 |
| Own perceptions/explanation of systemic issues | 17 |
| Learned something/“aha moment” | 11 |
| Emphasis on health (not climate change) | 9 |
| Individual behaviors | 8 |
| Perceived ignorance of others | 7 |
| Environmental triggers or causes of symptoms | 7 |
| Apathy about climate change/health | 5 |
| Avoidance/denial about climate change/health | 4 |
| Policy/government | 4 |
| Collective action | 2 |
| Clean energy/low pollution | 2 |
| Design | |
| Organization/layout | 20 |
| Appealing elements | 14 |
| Replace cartoons with photos of human faces/figures | 9 |
| Feature humans experiencing health effects | 9 |
| Suggestions for design | 9 |
| Suggestions for content | 9 |
| Color | 8 |
| Cartoons: appropriate for some | 8 |
| Cartoons: off-putting | 6 |
| Health literacy concerns | 5 |
| Cluttered/too much text | 1 |
Online survey respondent demographics and household health status (N = 122)
| Number | Percent | |
|---|---|---|
| Race/Ethnicity | ( | |
| White | 32 | 27.1 |
| Black | 34 | 28.8 |
| Hispanic | 21 | 17.8 |
| Other | 31 | 26.3 |
| Age | ( | |
| 18–24 | 18 | 15.0 |
| 25–34 | 49 | 40.8 |
| 35–44 | 39 | 32.5 |
| 45 and above | 14 | 11.7 |
| Gender | ( | |
| Female | 88 | 72.1 |
| Male | 34 | 27.9 |
| Education | ( | |
| Some high school | 8 | 6.7 |
| High school or GED | 20 | 16.7 |
| Some college/2-year degree | 92 | 76.7 |
| Income | ( | |
| Less than 20 K | 18 | 15.3 |
| 20 K–30 K | 24 | 20.3 |
| 31 K–40 K | 75 | 64.4 |
| State of Residence | ( | |
| California | 38 | 33.0 |
| Texas | 20 | 17.4 |
| Pennsylvania | 35 | 30.4 |
| Georgia | 12 | 10.4 |
| Ohio or Michigan (Midwest) | 10 | 8.7 |
| Household Health Conditions | ( | |
| Asthma | 69 | 59.0 |
| Pollen Allergies | 65 | 56.0 |
| Obesity | 33 | 28.5 |
| Diabetes | 17 | 14.7 |
| Health effects from extreme heat | 21 | 18.1 |
| Affected household members | ( | |
| Self | 81 | 69.8 |
| Partner | 28 | 24.1 |
| Parent | 37 | 31.9 |
| Other adult household member | 4 | 3.5 |
| Child | 12 | 10.3 |
Fig. 1Proportion of respondents (95 % CI) who correctly identified populations that are vulnerable to health effects from extreme heat at pre- and post-test (n = 116)
Fig. 2Proportion of respondents (95 % CI) who correctly identified environmental conditions that worsen allergies at pre- and post-test (n = 116)
Fig. 3Proportion of respondents reporting strength of certainty that climate change is happening (n = 115)
Fig. 4Proportion of respondents reporting belief that climate change is affecting the health of themselves or their households at pre- and post-test (n = 116)
Predictors of intentions to practice recommended behaviors. (all measures at post-test) (n = 94)
| Behavioral intention index score | ||
|---|---|---|
|
| β | |
| Knowledge of heat-vulnerable populations (summary score) | 0.28 (0.08)** | 0.37 |
| Strength of certainty about climate change | 0.09 (0.07) | 0.13 |
| Belief that climate change affects health of self/household | 0.52 (0.27) | 0.19 |
| Political orientation (ref: very liberal) | 0.10 (0.07) | 0.13 |
| Race/ethnicity (ref: White) | ||
| Black | 0.55 (0.25)* | 0.29 |
| Hispanic | 0.77 (0.28)* | 0.35 |
| Other | 0.19 (0.29) | 0.10 |
| State of residence (ref: California) | ||
| Texas | −0.20 (0.26) | −0.09 |
| Pennsylvania | −0.03 (0.23) | −0.01 |
| Georgia | −0.22 (0.30) | −0.08 |
| Ohio or Michigan (Midwest) | −0.76 (0.32)* | −0.27 |
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| Knowledge of pollen allergy triggers (summary score) | 0.26 (0.08)* | 0.31 |
| Strength of certainty about climate change | 0.07 (0.07) | 0.10 |
| Belief that climate change affects health of self/household | 0.57 (0.27) | 0.21 |
| Political orientation (ref: very liberal) | 0.11 (0.07) | 0.15 |
| Race/ethnicity (ref: White) | ||
| Black | 0.46 (0.25) | 0.24 |
| Hispanic | 0.51 (0.28) | 0.23 |
| Other | −0.09 (0.28) | −0.05 |
| State of residence (ref: California) | ||
| Texas | −0.18 (0.26) | −0.08 |
| Pennsylvania | −0.04 (0.23) | −0.02 |
| Georgia | −0.18 (0.30) | −0.06 |
| Ohio or Michigan (Midwest) | −0.81 (0.32)* | −0.28 |
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| Knowledge of asthma triggers (summary score) | 0.10 (0.10) | 0.11 |
| Strength of certainty about climate change | 0.09 (0.08) | 0.12 |
| Belief that climate change affects health of self/household | 0.60 (0.29)* | 0.22 |
| Political orientation (ref: very liberal) | 0.13 (0.07) | 0.17 |
| Race/ethnicity (ref: White) | ||
| Black | 0.50 (0.27) | 0.26 |
| Hispanic | 0.44 (0.29) | 0.20 |
| Other | −0.08 (0.31) | −0.04 |
| State of residence (ref: California) | ||
| Texas | −0.31 (0.28) | −0.15 |
| Pennsylvania | −0.17 (0.24) | −0.09 |
| Georgia | −0.38 (0.32) | −0.14 |
| Ohio or Michigan (Midwest) | −0.83 (0.34) | −0.29 |
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*p ≤ 0.05; **p ≤ 0.001