Vital Surveillances: Environmental Health Literacy Prevalence and Profiles among Shanghai Residents — Shanghai, China, 2020–2024

Between 2020 and 2024, we conducted five annual cross-sectional surveys in Shanghai. Eligible participants included residents aged 15–69 years who had resided in the study area for at least six months during the previous year; we excluded individuals living in group quarters, such as student dormitories or employee housing (6–7). To ensure representativeness and comparability across survey years, we employed multi-stage cluster random sampling (6–7).

Initially, we calculated the minimum sample size for each stratum using equation (1):

where z=1.96 (α=0.05), p=0.5 [environmental health literacy (EHL) prevalence assumed in the absence of prior data], re=0.15 (relative error), and deff=1.5 (design effect).

Next, we inflated this minimum to the final target sample size as equation (2):

Stratification was based on gender (male, female) and survey areas (urban, suburban), resulting in four strata (2×2). Assuming a 14% refusal rate, the required sample size was at least 1,127 participants each year. The 2020 Shanghai survey followed the 2013 and 2017 trial guidelines and oversampled older adults to reflect the city’s aging demographic structure. However, to align with the 2022 evaluation deadline of the Healthy China Initiative, the Ministry of Ecology and Environment issued updated national documents in 2021 (trial version) and 2022 (final version of the “Survey Protocol for Residents’ Environmental Health Literacy”). Beginning in 2021, Shanghai adopted the national protocol, which employed a younger age distribution standard. This methodological shift resulted in demographic differences between the 2020 baseline and subsequent survey years (2021–2024), though the 2021–2024 surveys maintained internal demographic consistency.

The questionnaire assessed socio-demographic characteristics and incorporated the 47-item Core Questionnaire for Assessing the EHL of Chinese Residents, developed by the Ministry of Ecology and Environment. Sampling procedures and scoring methods followed the supplemental materials and protocols previously reported (6–10). Across the five survey rounds, we obtained 11,672 questionnaires and retained 11,220 valid responses, yielding a response rate of 96.13%.

All statistical analyses were conducted using R version 4.2.2 (R Foundation for Statistical Computing, Auckland, New Zealand). Environmental health literacy scores are reported as mean±standard deviation with interquartile ranges (P25–P75). We assessed between-group differences in continuous scores using independent t-tests or one-way analysis of variance, while categorical differences in EHL levels were evaluated with χ² tests. To identify factors associated with EHL, we employed generalized linear models and multivariate logistic regression analyses.

We analyzed 11,220 valid questionnaires distributed across the five survey years: 3,720 in 2020, 3,180 in 2021, and 1,440 in each of 2022, 2023, and 2024. Table 1 presents the demographic characteristics of respondents, including areas, gender, age, ethnicity, education level, occupation, and per-capita monthly income. Significant differences across survey years were observed for age, education, occupation, and income distributions (P<0.05).

The overall mean EHL score was 59.87±16.76, falling below the 70-point threshold for adequate literacy. No significant differences emerged by survey areas (urban vs. suburban), gender, or ethnicity (P>0.05). Compared with the 2020 baseline (55.28±15.64), mean scores demonstrated consistent improvement: 61.77±15.92 in 2021, 62.13±17.14 in 2022, 62.03±16.97 in 2023, and 63.14±18.21 in 2024 (P<0.001). EHL scores followed an inverted-U pattern across age groups, peaking in middle age before declining (P<0.001). In contrast, scores increased monotonically with both education and income levels (both P<0.001) and varied significantly by occupation (P<0.001). Post-hoc analyses revealed no significant differences between laborers and other occupational groups, and between civil servants and students (P>0.05). Detailed results are presented in Supplementary Figure S1.

Adequate EHL was defined as a total score of ≥70 points. Across the five survey waves (2020–2024), 30.74% of participants achieved this threshold, with the proportion increasing steadily: 18.78% in 2020, 33.24% in 2021, 36.18% in 2022, 36.67% in 2023, and 44.72% in 2024 (P<0.001). However, Table 1 reveals a substantial shift in age distribution between 2020 and subsequent years. The 2020 survey reflected Shanghai’s actual population structure (aged 15–69 years), whereas the 2021–2024 surveys adopted a younger national standard. To preserve validity and isolate temporal trends from demographic shifts, we age-standardized the 2021–2024 estimates to Shanghai’s 2020 age composition. Age-adjusted EHL demonstrated significant improvement: 18.78% (2020), 30.18% (2021), 33.22% (2022), 33.84% (2023), and 42.88% (2024). The lower age-standardized rates compared with crude rates reflect the down-weighting of younger respondents when applying the 2020 reference population, which contained a higher proportion of elderly individuals. Urban residents demonstrated higher literacy than their suburban counterparts (32.00% vs. 29.41%), while men achieved marginally higher rates than women (31.85% vs. 29.63%). Age exhibited an inverted-U pattern, with literacy peaking at 40.41% among individuals aged 18–34 years before declining to 20.45% in the 50–69 years age group. Education displayed a clear dose–response gradient: only 13.18% of participants with primary schooling or less achieved adequate EHL, compared with 47.00% of those with postgraduate education (P<0.001). Complete demographic breakdowns are presented in Table 2.

Classification EHL level represents the proportion of participants whose score in a given domain achieved or exceeded 70% of the maximum possible score for that domain. The survey evaluated three first-level domains — basic concepts, basic knowledge, and basic skills — alongside six second-level domains: basic cognition, basic attitudes, fundamental concepts, scientific knowledge, basic behavior, and basic skills. Figure 1 presents the temporal trends for both first- and second-level domains across 2020–2024. Among the first-level domains (Figure 1A), basic concepts exhibited an initial increase followed by a temporary decline before rising again, whereas basic skills maintained consistently high levels with minimal variation. In contrast, basic knowledge demonstrated the most substantial improvement, increasing markedly from 7.12% in 2020 to 19.81%, 34.58%, 37.08%, and 39.93% in 2021–2024, respectively. At the second-level (Figure 1B), basic cognition remained relatively stable near 20% throughout the study period, while scientific knowledge, fundamental concepts, and basic skills all showed considerable improvement compared with baseline measurements in 2020.

Figure 1. 

Proportion of Shanghai residents achieving adequate EHL, 2020–2024. (A) Overall EHL and its three first-level components; (B) Six second-level components.

Note: Error bars represent the standard error, calculated as $ \sqrt{p(1-p)/n} $, in which p=EHL level and n=sample size.

Abbreviation: EHL=Environmental Health Literacy.

EHL is influenced by survey year, survey area, gender, age, education, occupation and income. After adjusting for potential confounders, multivariate generalized-linear and logistic regression models were employed.

Compared with 2020, mean EHL in 2024 was 7.87 points higher (95% CI: 6.87, 8.87). Urban residents scored 1.78 points higher than suburban residents (95% CI: 1.07, 2.50). The youngest age group (15–34 years) outperformed the oldest (50–69 years) by 9.42 points (95% CI: 8.06, 10.79), and the highest-education group exceeded the lowest by 15.54 points (95% CI: 13.03, 18.05). Civil servants and senior managers scored 10.66 points higher than farmers (95% CI: 9.15, 12.18), while the middle-income band (CNY 13,000–21,000) scored 6.56 points above the lowest-income group (95% CI: 5.41, 7.71) (Figure 2A).

Figure 2. 

Determinants of EHL in Shanghai, 2020–2024. (A) Change in mean EHL score (generalized-linear model); (B) Odds of achieving adequate EHL (multivariate logistic regression).

Abbreviation: CI=confidence interval; EHL=Environmental Health Literacy; CNY=Chinese Yuan.

In the logistic model, participants in 2024 were 3.50 times more likely to achieve adequate EHL than those in 2020 (OR=3.50; 95% CI: 3.07, 4.00). Suburban residents had lower odds than urban residents (OR=0.89; 95% CI: 0.82, 0.96), as did women compared with men (OR=0.90; 95% CI: 0.83, 0.98). Relative to the youngest group, the oldest had markedly lower odds (OR=0.39; 95% CI: 0.33, 0.46), whereas the highest-education group demonstrated nearly six-fold greater odds (OR=5.85; 95% CI: 4.08, 8.36) (Figure 2B).

By 2020, 18.78% of Shanghai residents had already surpassed the 2022 national target of 15% established by the Healthy China Initiative (2019–2030) (11). This baseline figure exceeded contemporaneous statistics from Shaanxi (17.6%) (8), Hubei (17.4%) (10), and the initial 2020 national survey (12.5%) (12), while closely approximating the second national survey conducted in 2022 (18.8%) (13). When compared with the 2022 national survey results, Shanghai residents demonstrated substantially higher overall EHL (36.18% vs. 18.8%) and superior performance in both basic knowledge (34.58% vs. 14.1%) and basic skills (43.14% vs. 25.7%) (13). However, performance in basic concepts lagged slightly behind national levels (31.94% vs. 36.1%). Among second-level domains, basic cognition (23.68%) and scientific knowledge (26.94%) remained the principal areas requiring improvement (13), though both approached the 2030 national threshold of 25% (11). Across occupational categories, farmers exhibited the lowest EHL levels, whereas civil servants and organizational leaders recorded the highest, reflecting underlying educational disparities. Although men achieved slightly higher scores than women (31.85% vs. 29.63%), this gender gap was substantially narrower than that observed in Shaanxi (25.0% vs. 11.5%) (8) or Hubei (20.6% vs. 15.8%) (10), likely attributable to higher educational attainment among women in Shanghai. Similarly, the suburban–urban disparity (29.4% vs. 32.0%) was less pronounced than that documented in Shaanxi (8), Hubei (10), or the 2022 national survey (13), indicating more balanced regional development in Shanghai.

Although demographic characteristics varied across survey years (Table 1), Spearman correlation analyses revealed moderate negative associations between age and education (r=–0.38) and weak positive associations between age and both occupation and income (r=0.14 and 0.17, respectively). These correlations demonstrate that age is interrelated with education, occupation, and income. Age standardization was therefore employed to control for these socioeconomic differences across survey years. Furthermore, these correlations indicate that older residents tend to have lower educational attainment, are more likely to work in agriculture, and earn less — explaining why education emerges as the dominant determinant of EHL. This finding mirrors earlier research demonstrating that low educational attainment predicts higher mortality, with income serving as a key mediator (14–15); improving EHL may therefore help offset these risks by promoting healthier environments (2).

To sustain and further enhance EHL, Shanghai should prioritize health promotion and surveillance among vulnerable populations — specifically older adults, individuals with limited education or income, and agricultural workers — while focusing educational content on fundamental environment-health relationships and scientific knowledge regarding air quality, water safety, soil contamination, ocean health, biodiversity conservation, and climate change. Future EHL improvement initiatives should employ tailored dissemination strategies for different target audiences. For instance, short, accessible videos on environmental health topics can be delivered through social media platforms such as TikTok to reach older adults who regularly use these applications, whereas informational displays in subway stations and transit systems can effectively target commuters and office workers.

This study’s principal strength lies in its five-year series of repeated cross-sectional surveys conducted in a large, representative sample, yielding actionable evidence for public health interventions. The primary limitation stems from the shift in age composition between the 2020 baseline and subsequent 2021–2024 surveys. Given Shanghai’s older demographic structure, nationally age-standardized crude EHL rates for 2022–2024 overestimate city-level literacy. Consequently, locally age-standardized rates provide a more accurate measure of Shanghai-specific improvements in EHL. Additionally, unregistered renters were excluded from sampling; a targeted survey of this population is needed to fully assess the equity and reach of current health-promotion initiatives.

Using baseline data from 2020, we designed targeted interventions that prioritized suburban residents, older adults, and individuals with low income or education levels, delivering tailored content to each group. Core educational messages encompassed fundamental environment-health interactions, regulatory standards, water quality, environmental toxicants, air pollution, and climate change. We employed multimodal, audience-specific dissemination channels — including print media, newspapers, and paper-based materials for older adults — to address identified knowledge gaps. Five consecutive city-wide surveys demonstrated a significant monotonic increase in age-standardized EHL: 18.78% (2020), 30.18% (2021), 33.22% (2022), 33.84% (2023), and 42.88% (2024). The most substantial gains occurred in the first post-intervention year, with continued improvements observed in subsequent years. These findings substantiate the effectiveness of Shanghai’s environmental health education campaigns.

The field teams from the district-level Centers for Disease Control and Prevention and the community health service centers for their meticulous data collection. We are also grateful to all Shanghai residents who participated in these surveys.

Approved by the Shanghai Municipal Center for Disease Control and Prevention (approval No. 2020-94).