- Research article
- Open Access
Regional-level risk factors for severe hand-foot-and-mouth disease: an ecological study from mainland China
Environmental Health and Preventive Medicine volume 26, Article number: 4 (2021)
Severe hand-foot-and-mouth disease (HFMD) is a life-threatening contagious disease among young children and infants. Although enterovirus A71 has been well acknowledged to be the dominant cause of severe HFMD, there still remain other unidentified risk factors for severe HFMD. Previous studies mainly focused on identifying the individual-level risk factors from a clinical perspective, while rare studies aimed to clarify the association between regional-level risk factors and severe HFMD, which may be more important from a public health perspective.
We retrieved the clinical HFMD counts between 2008 and 2014 from the Chinese Center for Disease Control and Prevention, which were used to calculated the case-severity rate in 143 prefectural-level cities in mainland China. For each of those 143 cities, we further obtained city-specific characteristics from the China City Statistical Yearbook (social and economic variables) and the national meteorological monitoring system (meteorological variables). A Poisson regression model was then used to estimate the associations between city-specific characteristics (reduced by the principal component analysis to avoid multicollinearity) and the case-severity rate of HFMD. The above analysis was further stratified by age and gender to examine potential modifying effects and vulnerable sub-populations.
We found that the case-severity rate of HFMD varied dramatically between cities, ranging from 0 to 8.09%. Cities with high case-severity rates were mainly clustered in Central China. By relating the case-severity rate to city-specific characteristics, we found that both the principal component characterized by a high level of social and economic development (RR = 0.823, 95%CI 0.739, 0.916) and another that characterized by warm and humid climate (RR = 0.771, 95%CI 0.619, 0.960) were negatively associated with the case-severity rate of HFMD. These estimations were consistent across age and gender sub-populations.
Except for the type of infected pathogen, the case-severity rate of HFMD was closely related to city development and meteorological factor. These findings suggest that social and environmental factors may also play an important role in the progress of severe HFMD.
Hand-foot-and-mouth disease (HFMD) is a contagious disease caused by the enterovirus. Most cases of HFMD are mild and self-limited, but a small proportion could further develop to severe complications affecting the central nervous systems [1, 2]. Due to its rapid progression and the lack of effective antiviral medications [3,4,5], the prognosis of severe HFMD cases is usually poor [6, 7]. Patients often suffer due to high medical expenses  and poor quality of life . Enterovirus A71 (EV-A71) has been shown to be the dominant pathogen causing severe HFMD [1, 10]. Approximately 80% and 95% of severe and fatal cases test positive for EV-A71, respectively [1, 11]. However, among the EV-A71 infected cases, only 23.88% and 1.89% develop into severe and fatal cases , implying that there still remain other unidentified risk factors for severe HFMD.
The overwhelming majority of prior studies mainly focused on examining the associations between severe HFMD and individual-level risk factors, such as individual demographic characteristics, early clinical manifestations, and genetic susceptibility. It has been found that younger  and male sex  were more vulnerable to severe HFMD, while breastfeeding and hand washing after playing  were found to be protective. Clinical manifestations including high fever, vomiting, myoclonic twitching, and elevated serum interleukins and interferon-γ levels were found to be early indicators of severe cases . The presence of the rs4290270 SNP in the TPH2 gene was associated with increased susceptibility to severe HFMD .
Although those above individual-level studies have provided important insights for identifying high-risk individuals from a clinical perspective, there is still an urgent need to clarify the associations between regional-level risk factors and severe HFMD. This would provide a deeper understanding of why severe HFMD cases are more likely to occur in specific regions, and then provide evidences on how to better control severe HFMD from a public health perspectives. To the best of our knowledge, rare studies have paid special attention to the associations between regional-level risk factors and severe HFMD [18,19,20,21]. Only a few studies sporadically reported higher population density , rural living , and lower socioeconomic status  would raise the epidemic of severe HFMD. In fact, there were remaining other regional-level factors should be considered when estimating their impact on epidemic of severe HFMD, such as medical resource allocation, meteorological features, GDP, and population scale. Notably, previous studies were mainly limited in a specific province, and a nationwide study covering multidimensional factors is still in lack.
Therefore, to address the above research gap, we conducted this nationwide study including 143 prefectural-level cities and abundant city-level characteristics to identify regional-level risk factors for the severe HFMD.
In the current study, the observational units were cities in mainland China. For each city, the city-specific characteristics and case-severity rate were used as the covariates and outcome, respectively. City selection was based on the availability of meteorological covariates and the case-severity rate. The case-severity rate was calculated for 293 cities in mainland China based on daily counts of HFMD clinical cases . Meteorological covariates were collected from 646 national ground meteorological stations through the China Meteorological Data Sharing Service System. After matching meteorological stations with their corresponding cities, 143 cities were included in the current study [22, 23]. Each of those 143 cities was further defined as the main central urban area in each prefecture (i.e., the prefectural-level city) . This is because prefecture-level cities usually have a larger population which is more important for infectious disease control. Additionally, when compared with small cities, the prefecture-level cities have better surveillance systems that can guarantee data quality.
City-specific case-severity rate of HFMD
The city-specific case-severity rate was chosen as the outcome variable due to its representation of the regional disease burden of severe HFMD . It was defined as the total number of severe cases divided by the total number of probable cases from 1 January 2008 to 30 December 2014. Severe cases were defined as clinical cases with any CNS complications, cardiopulmonary dysfunction, or both. Probable cases were defined as patients with a papular or vesicular rash on the hands, feet, mouth, or buttocks, with or without fever . All cases were collected from the daily counts of clinical HFDM cases through the China Information System for Disease Control and Prevention. Using this system, other variables, including patient age, gender, enterovirus serotypes, time from symptom onset to diagnosis, and severity (mild or severe), were also extracted. In addition, as over 99% of HFMD cases occurred among children under the age of 12 years (i.e., children in elementary school and below) according to our preliminary analysis . Therefore, in the current study, we mainly focused on the incidence of HFMD among children aged 0–12 years.
The starting point of the observation period was 1 January 2008, as all probable and laboratory-confirmed HFMD cases were required to be reported to the Chinese Centre for Disease Control and Prevention (China CDC) since 1 January 2008 , before when relevant data were not available. The endpoint was set at 30 December 2014 because the EV71 vaccine was approved for marketing on 3 December 2015 , after when the epidemiology of HFMD might has become altered.
The city-specific characteristics mainly included socioeconomic and meteorological variables. The socioeconomic variables were collected from the China City Statistical Yearbook  including demographic variables (population density and rate of population increase), economic variables (GDP per person and rate of GDP increase), health resources (number of licensed physicians, hospital beds, and hospitals per 1000 persons), traffic (total travel passengers per year), number of elementary school students per 1000 persons, and per capita public green areas. Meteorological variables, including relative humidity, temperature, rainfall, and sunshine hours, were extracted from daily meteorological monitoring data. Arithmetic means for meteorological variables were calculated for each 143 cities to exhibit the city level meteorological differences.
Comparisons of city-specific characteristics between city groups
To answer why severe HFMD cases prone to occur at specific regions, two city groups were defined. Cities with a high case-severity and a low incidence were classified as severe HFMD burdened areas (ranked 51–100% in case-severity rate, and 1–50% in incidence). Cities with a low case-severity rate and a high incidence were classified as less burdened areas (ranked 1–50% in case-severity rate, and 51–100% in incidence). Then comparisons of city-specific characteristics between these two groups were conducted.
Dimensionality reduction of city-specific characteristics
To reduce multicollinearity, city-specific covariates with a variance inflation factor (VIF) ≥ 5  were compressed by principal component analysis (PCA)  (see Additional file 1: Table S2 for the variance inflation factor (VIF) of each city-specific variable). New variables (principal components, PCs) and city-specific covariates with a VIF < 5 were used as regressors in the subsequently generated core model.
Estimating associations between case-severity rate and city-specific characteristics
A Poisson regression was applied to examine the associations between the case-severity rate and city-specific characteristics. The principal components and city-specific variables (VIF < 5) were the regressors, the cumulative number of severe cases during the observation period was the outcome, and the natural logarithm of the corresponding probable cases was the offset.
Stratification analysis on gender and age-group were further carried out based on the core model. Gender and age were the most important demographic characteristics [1, 28] [29,30,31,32,33,34]; therefore, stratification analyses on gender and age were used to identify potential vulnerable sub-populations. The cutoff value of age group was 2 years old (age ≥ 2 years vs. age < 2 years), as 2 years has been observed to be the peak age of both incidence and severity-case rate [1, 28].
All statistical analyses were performed using R software (Version 3.6.1; R Core Team, 2019), mainly using the packages “GLM” and “principal.” Spatial distribution maps of HFMD incidence and case-severity rate were made using ArcGIS Pro (version 2.4, authorization number: EFL734321752).
Spatial distribution of case-severity rate and incidence of HFMD
In the current analysis, 143 cities were included, covering the majority of the medium and large size cites cities in mainland China. A total of 3,656,006 probable cases, including 27,690 severe cases (cases-severity risk 0.76%) were observed in the period from 2008 to 2014. The 7-year cumulative incidence of HFMD ranged from 11.70 per million to 744.97 per million, and the case-severity rate ranged from 0 to 8.09%. Discrepant spatial distributions of the case-severity rate and HFMD incidence were observed. High HFMD incidence was observed in the Pearl River Delta and the South Area (Fig. 1a), while high case-severity rates were observed was in Central China, including Henan, Shandong, and Shanxi provinces (Fig. 1b).
Comparison of city-specific characteristics between severe HFMD burdened and less burdened areas
There were 30 cities classified into severe HFDM burdened areas, and 30 cities into the less burdened areas (see Additional file 1: Table S1 for classification of severe HFMD burdened and less burdened areas). Comparisons between those two areas revealed that severe HFMD burdened areas had lower GDP and GDP per person, lower population density, fewer licensed doctors, fewer per capita public green areas, lower average temperature, and less average rainfall (Table 1).
Associations between case-severity rate and city-specific characteristics
City development and meteorological indicators were two principal components generated by PCA. The city development indicator was characterized by high levels of social and economic development level and accounted for 66% of the total variance. The meteorological indicator was characterized by warm and humid climate and accounted for 34% of the total variance. The case-severity rate of HFMD was negatively associated with GDP increase rate (RR = 0.745, P = 0.009), city development indicator (RR = 0.823 P < 0.001), and meteorological indicator (RR = 0.771, P = 0.022) (Table 2).
Stratification analysis by gender and age group
In the stratification analysis by gender, the results of the core model were consistent. Both in the male and female sub-populations, the GDP increase rate, city development indicator, and meteorological feature were all significantly negatively correlated with the case-severity rate (Table 3, Fig. 2a). When stratified by age, the results of the core model were also consistent. In the two age groups, the GDP increase rate, city development indicator, and meteorological feature were all significantly negatively correlated to the case-severity rate (Table 4, Fig. 2b).
Using nationwide data on severe HFMD, we observed the city-specific characteristics were related to regional differences in the case-severity rate. Our main findings suggest that beyond the type of infected pathogen, attention to social and environmental factors is necessary for controlling epidemics of severe HFMD. In addition, based on the spatial distribution of the case-severity rate and incidence, we found that areas of high HMFD incidence were mainly in the Pearl River Delta and South China, while areas of high case-severity rates were mainly located in Central China.
The city development indicator was negatively associated with the case-severity rate, indicating case-severity rate was higher in areas with lower economic development and insufficient medical resources. This phenomenon might be due to that the rural living [35, 36], lower socioeconomic status , and insufficient medical capacity  are more common in less developed areas. Poor personal hygiene, insufficient knowledge of disease, and delayed therapy increase the number of severe HFMD cases, thus resulting in a higher case-severity rate. Therefore, we suggest increasing the allocation of local medical resources and improving accessibility, as this might reduce the regional disease burden of severe HFMD.
We found that the meteorological feature indicator representing a warm and humid climate was negatively associated with the case-severity rate. One possible explanation might be that in a warm and humid climate, an increase of probable cases will be more pronounced than the increase of severe cases. At present, most of the researches support the idea that the number of probable cases would increase in a warm and humid climate [22, 38,39,40]. This is because higher temperatures may increase host activity, resulting in more frequent contact between infected and susceptible individuals. On humid days, enteroviruses can be easily attached to the small articles in the air, resulting in easier transmission of enteroviruses . In addition, on sunny days, ultraviolet radiation could lead to inactivation of enteroviruses [39, 41]. However, the increase in severe cases would be less obvious than the increase in probable cases. This is because progression to severe HFMD not is only determined by enteroviral infection, but also depends on individual immunity  and medical treatment . Therefore, in a warm and humid climate, a faster increase of total HFMD cases would accompanied by a decreased case-severity rate.
Previous studies have shown that both HFMD incidence  and case-severity rate  were positively correlated with the population density, while this relationship is non-significant in severe HFMD incidence . In the current study, we found that the relationship between population density and the case-severity rate was non-significant. This might for the following reasons: first, we hypothesized that two opposing forces might drive the relationship between population density and case-severity rate. On the one hand, more densely populated areas typically have better socioeconomic status and sufficient medical resources. Children in those areas are often better cared by more educated caregivers (resulting in lower case-severity rate). On the other hand, more densely populated areas have a higher severe HFMD detection rate with more sufficient medical facilities (resulting in a higher case-severity rate). Therefore, given both of these trends, the relationship between population density and case-severity rate might be non-significant. Moreover, based on the interpretation of statistical modeling, the non-significance of the population density indicates its impact on the case-severity rate was weaker than the impact from the city development and meteorological indicators. Therefore, we suggest that in addition to physical isolation measures, adequate health resources and timely treatment are crucial for controlling severe HFMD.
This study had two major strengths. First, this is a city-level study. Unlike the individual-level studies focusing on the diagnosis and treatment of clinical cases, results from the current study are crucial for public health decision-making. Second, this is a nationwide study with multiple covariates, which can provide a stable estimation on the associations between case-severity rate and city-specific characteristics.
This study has four main limitations. The first one is the intrinsic nature of ecological study. Conclusions from the current study were based on the population scale, inference on other situations should be careful. The second limitation is related to the data quality. Since our data was collected from surveillance data, under-reporting from surveillance data might introduce extra basis. However, the cumulative numbers from 2008 to 2014 were used as outcome, which are more reliable than single observations under mild under-reporting conditions. The third limitation is that the city-specific EV-A71 infection rate was not included in the core model. This is because that laboratory-based diagnosis of HFMD was only available in a small fraction of the total HFMD cases. Therefore, city-specific EV-A71 infection rate were not available. The final limitation is the study period, which did not extend into most recent years. As the EV71 vaccine was approved for marketing on 3 December 2015 , the epidemiology of HFMD has since changed. Further studies comparing those associations before and after the introduction of the vaccine are necessary.
In conclusion, the case-severity rate is an indicator of severe HFMD disease burden, unlike the incidence of HFMD, which is mainly affected by enterovirus, meteorological factors, and population density. The case-severity rate was closely related to medical resource allocation and the level of city development. Enhancing the medical resource allocation and improving it accessibility among rural population might result in improved disease prevention and control.
Availability of data and materials
The meteorological data used in the study are available from the China Meteorological Data Network (http://data.cma.cn/en). The Socioeconomic data used in the study are available from the statistical yearbook (http://www.stats-sd.gov.cn/). Other data is available from the corresponding author on reasonable request.
Center for Disease Control
Gross domestic product
Xing WJ, Liao QH, Viboud C, Zhang J, Sun JL, Wu JT, et al. Hand, foot, and mouth disease in China, 2008-12: an epidemiological study. Lancet Infect Dis. 2014;14:308–18.
Huang J, Liao Q, Ooi MH, Cowling BJ, Chang Z, Wu P, et al. Epidemiology of recurrent hand, foot and mouth disease, China, 2008-2015. Emerg Infect Dis. 2018;24:432–42.
Pan J, Chen M, Zhang X, Chen Y, Liu H, Shen W. High risk factors for severe hand, foot and mouth disease: a multicenter retrospective survey in Anhui Province China, 2008-2009. Indian J Dermatol. 2012;57:316–21.
Cox B, Levent F. Hand, Foot, and Mouth Disease. Jama. 2018;320:2492.
Liu G, Xu Y, Wang X, Zhuang X, Liang H, Xi Y, et al. Developing a machine learning system for identification of severe hand, foot, and mouth disease from electronic medical record data. Scientific Reports. 2017;7.
Huang MC, Wang SM, Hsu YW, Lin HC, Chi CY, Liu CC. Long-term cognitive and motor deficits after enterovirus 71 brainstem encephalitis in children. Pediatrics. 2006;118:e1785–8.
Chang LY, Huang LM, Gau SS, Wu YY, Hsia SH, Fan TY, et al. Neurodevelopment and cognition in children after enterovirus 71 infection. N Engl J Med. 2007;356:1226–34.
Zheng YM, Yang J, Liao QH. Direct medical costs and influencing factors in severe hand, foot and mouth disease in children aged between six months and five years old. Zhonghua Yu Fang Yi Xue Za Zhi. 2017;51:87–92.
Zheng YM, Yang J, Liao QH. Health related quality of life on severe hand, foot and mouth disease patients. Zhonghua Liu Xing Bing Xue Za Zhi. 2017;38:462–6.
Chen SC, Chang HL, Yan TR, Cheng YT, Chen KT. An eight-year study of epidemiologic features of enterovirus 71 infection in Taiwan. Am J Trop Med Hyg. 2007;77:188–91.
Nhan LNT, Hong NTT, Nhu LNT, Nguyet LA, Ny NTH, Thanh TT, et al. Severe enterovirus A71 associated hand, foot and mouth disease, Vietnam, 2018: preliminary report of an impending outbreak. Euro Surveill. 2018;23.
Qiu J, Yan H, Cheng N, Lu X, Hu X, Liang L, et al. The clinical and epidemiological study of children with hand, foot, and mouth disease in Hunan, China from 2013 to 2017. Sci Rep. 2019;9:11662.
Yang X, Li Y, Zhang C, Zhan W, Xie J, Hu S, et al. Clinical features and phylogenetic analysis of severe hand-foot-and-mouth disease caused by Coxsackievirus A6. Infect Genet Evol. 2020;77:104054.
Crabol Y, Pean P, Mey C, Duong V, Richner B, Laurent D, et al. A prospective, comparative study of severe neurological and uncomplicated hand, foot and mouth forms of paediatric enterovirus 71 infections. Int J Infect Dis. 2017;59:69–76.
Li Y, Xiong T, Meng Y, Zhao R, Yu G, Liu J, et al. Risk factors for severe hand, foot, and mouth disease infected with Coxsackievirus A6: A hospital-based case-control study. J Med Virol. 2020. https://doi.org/10.1002/jmv.26343.
Cai K, Wang Y, Guo Z, Yu H, Li H, Zhang L, et al. Clinical characteristics and managements of severe hand, foot and mouth disease caused by enterovirus A71 and coxsackievirus A16 in Shanghai, China. BMC Infect Dis. 2019;19:285.
Meng Y, Xiong T, Zhao R, Liu J, Yu G, Xiao J, et al. Genome-wide association study identifies TPH2 variant as a novel locus for severe CV-A6-associated hand, foot, and mouth disease in Han Chinese. Int J Infect Dis. 2020;98:268–74.
Wang Y, Zhao H, Ou R, Zhu H, Gan L, Zeng Z, et al. Epidemiological and clinical characteristics of severe hand-foot-and-mouth disease (HFMD) among children: a 6-year population-based study. BMC Public Health. 2020;20:801.
Ji H, Fan H, Lu PX, Zhang XF, Ai J, Shi C, et al. Surveillance for severe hand, foot, and mouth disease from 2009 to 2015 in Jiangsu province: epidemiology, etiology, and disease burden. BMC Infect Dis. 2019;19:18.
Yu S, Zhou Z, Yang F, Xiao G, Ma J. Temporal and spatial clustering characteristics and changes of severe hand, foot, and mouth disease in mainland of China, from 2008 to 2013. Zhonghua Liu Xing Bing Xue Za Zhi. 2014;35:271–5.
Chen SM, Qin L, Du ZH, Jin YM, Du JW, Chen Y, et al. Spatial clustering of severe hand-foot-mouth disease cases on Hainan Island, China. Jpn J Infect Dis. 2017;70:604–8.
Xiao X, Gasparrini A, Huang J, Liao Q, Liu F, Yin F, et al. The exposure-response relationship between temperature and childhood hand, foot and mouth disease: A multicity study from mainland China. Environ Int. 2017;100:102–9.
Bo Z, Ma Y, Chang Z, Zhang T, Liu F, Zhao X, et al. The spatial heterogeneity of the associations between relative humidity and pediatric hand, foot and mouth disease: Evidence from a nation-wide multicity study from mainland China. Sci Total Environ. 2020;707:136103.
Mao QY, Wang Y, Bian L, Xu M, Liang Z. EV71 vaccine, a new tool to control outbreaks of hand, foot and mouth disease (HFMD). Expert Rev Vaccines. 2016;15:599–606.
National Bureau of Statistics of China. National census in China, 2010. http://www.stats.gov.cn/tjsj/ndsj/2011/indexch.htm (Accessed on 23 Sep 2012).).
Akinwande MO, Dikko HG, Samson A. Variance inflation factor: as a condition for the inclusion of suppressor variable(s) in regression analysis. Open Journal of Statistics. 2015;05(07):14.
Ivosev G, Burton L, Bonner R. Dimensionality reduction and visualization in principal component analysis. Anal Chem. 2008;80:4933–44.
Liu XF, Sun XM, Sun XW, Yang YQ, Huang CH, Wen H. Epidemiological study on hand, foot and mouth disease in Tongzhou District, Beijing, 2013-2017. J Int Med Res. 2019;47:2615–25.
Wang YR, Sun LL, Xiao WL, Chen LY, Wang XF, Pan DM. Epidemiology and clinical characteristics of hand foot, and mouth disease in a Shenzhen sentinel hospital from 2009 to 2011. BMC Infect Dis. 2013;13:5.
Samphutthanon R, Tripathi NK, Ninsawat S, Duboz R. Spatio-temporal distribution and hotspots of hand, foot and mouth disease (HFMD) in Northern Thailand. Int J Environ Res Public Health. 2014;11:312–36.
Chan KP, Goh KT, Chong CY, Teo ES, Lau G, Ling AE. Epidemic hand, foot and mouth disease caused by human enterovirus 71, Singapore. Emerg Infect Dis. 2003;9:78–85.
Wang J, Cao Z, Zeng DD, Wang Q, Wang X, Qian H. Epidemiological analysis, detection, and comparison of space-time patterns of Beijing hand-foot-mouth disease (2008-2012). PLoS One. 2014;e92745:9.
Puenpa J, Mauleekoonphairoj J, Linsuwanon P, Suwannakarn K, Chieochansin T, Korkong S, et al. Prevalence and characterization of enterovirus infections among pediatric patients with hand foot mouth disease, herpangina and influenza like illness in Thailand, 2012. PLoS One. 2014;9:e98888.
Wang Y, Feng Z, Yang Y, Self S, Gao Y, Longini IM, et al. Hand, foot, and mouth disease in China: patterns of spread and transmissibility. Epidemiology. 2011;22:781–92.
Qin L, Dang D, Wang X, Zhang R, Feng H, Ren J, et al. Identification of immune and metabolic predictors of severe hand-foot-mouth disease. Plos One. 2019;14.
Zhang D, Li R, Zhang W, Li G, Ma Z, Chen X, et al. A case-control study on risk factors for severe hand, foot and mouth disease. Scientific Reports. 2017;7.
Liu S-L, Pan H, Liu P, Amer S, Chan T-C, Zhan J, et al. Comparative epidemiology and virology of fatal and nonfatal cases of hand, foot and mouth disease in mainland China from 2008 to 2014. Reviews in Medical Virology. 2015;25:115–28.
Cheng Q, Bai L, Zhang Y, Zhang H, Wang S, Xie M, et al. Ambient temperature, humidity and hand, foot, and mouth disease: a systematic review and meta-analysis. Science of the Total Environment. 2018;625:828–36.
Coates SJ, Davis MDP, Andersen LK. Temperature and humidity affect the incidence of hand, foot, and mouth disease: a systematic review of the literature - a report from the International Society of Dermatology Climate Change Committee. Int J Dermatol. 2019;58:388–99.
Phung D, Nguyen HX, Nguyen HLT, Do CM, Tran QD, Chu C. Spatiotemporal variation of hand-foot-mouth disease in relation to socioecological factors: a multiple-province analysis in Vietnam. Sci Total Environ. 2018;610-611:983–91.
Bertrand I, Schijven JF, Sánchez G, Wyn-Jones P, Ottoson J, Morin T, et al. The impact of temperature on the inactivation of enteric viruses in food and water: a review. J Appl Microbiol. 2012;112:1059–74.
Chen S, Yang Y, Yan X, Chen J, Yu H, Wang W. Influence of vitamin A status on the antiviral immunity of children with hand, foot and mouth disease. Clin Nutr. 2012;31:543–8.
The authors thank the Chinese Center for Disease Control and Prevention for providing data.
This study was primarily sponsored by the National Natural Science Foundation of China (grant number 81903415) and the Key R&D Project of Sichuan Province Science and Technology Support Program (grant number 2020YFS0215). Xing Zhao was supported by the National Natural Science Foundation of China (grant number U1903123, and 81773548).
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Classification of severe HFMD burdened and less burdened groups for the 143 cities. Table S2 Variance inflation factor for city-specific characteristics. Table S3 Principal component loadings on part of city-specific characteristics. Figure S1 Visualization of the principal component analysis. A. The principal component loadings of the first three principal components. B. The map of variable-categorizing based on the first two principal components (PC_1, PC_2 correspond to the City development and Meteorological features, respectively.). Table S4 The Poisson regression model for associations between city characteristics and case-severity rate in male cases. Table S5 The Poisson regression model for associations between city characteristics and case-severity rate in female cases. Table S6 The Poisson regression model for associations between city characteristics and case-severity rate in patients under two years. Table S7 The Poisson regression model for associations between city characteristics and case-severity rate in patients above and equal to two years
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Pan, Q., Liu, F., Zhang, J. et al. Regional-level risk factors for severe hand-foot-and-mouth disease: an ecological study from mainland China. Environ Health Prev Med 26, 4 (2021). https://doi.org/10.1186/s12199-020-00927-9
- Hand, foot and mouth disease
- Case-severity rate
- City-specific characteristics
- Ecological study