Symptom cluster among cancer survivors from a nationally representative survey: a network analysis.

PURPOSE: To identify the symptom cluster among cancer survivors and examine their subgroup differences via network analysis based on nationally representative data. METHODS: This cross-sectional study included 2966 survivors participating in the 2020 National Health Interview Survey (NHIS). Participants self-reported the presence of 14 symptoms capturing four clusters (physical, somatic, sleep, and psychologic problems). Network analysis models were used to reveal the relationships between symptoms and those interactions. Network comparison tests were applied to compare subgroups. RESULTS: The core symptoms of the symptom cluster were fatigue (Bet = 33, Clo = 0.0067, Str = 0.9397), pain (Bet = 11, Clo = 0.0060, Str = 0.9226), wake up well rested (Bet = 25, Clo = 0.0057, Str = 0.8491), and anxiety (Bet = 5, Clo = 0.0043, Str = 0.9697) among cancer survivors. The core symptoms, network structure, and global strength were invariant between time since diagnoses (< 2 years vs. ≥ 2 years) or between numbers of cancers (1 vs. ≥ 2), yet varied between the comorbidity group and non-comorbidity group (≥ 1 vs. 0). CONCLUSIONS: Fatigue would be a potential target for alleviating other symptoms through a negative feedback loop of other related symptoms of cancer survivors. In particular, cancer survivors with other chronic diseases should be the focus of attention and strengthen targeted intervention.

Identifying vital sign trajectories to predict 28-day mortality of critically ill elderly patients with acute respiratory distress syndrome.

BACKGROUND: The mortality rate of acute respiratory distress syndrome (ARDS) increases with age (≥ 65 years old) in critically ill patients, and it is necessary to prevent mortality in elderly patients with ARDS in the intensive care unit (ICU). Among the potential risk factors, dynamic subphenotypes of respiratory rate (RR), heart rate (HR), and respiratory rate-oxygenation (ROX) and their associations with 28-day mortality have not been clearly explored. METHODS: Based on the eICU Collaborative Research Database (eICU-CRD), this study used a group-based trajectory model to identify longitudinal subphenotypes of RR, HR, and ROX during the first 72 h of ICU stays. A logistic model was used to evaluate the associations of trajectories with 28-day mortality considering the group with the lowest rate of mortality as a reference. Restricted cubic spline was used to quantify linear and nonlinear effects of static RR-related factors during the first 72 h of ICU stays on 28-day mortality. Receiver operating characteristic (ROC) curves were used to assess the prediction models with the Delong test. RESULTS: A total of 938 critically ill elderly patients with ARDS were involved with five and 5 trajectories of RR and HR, respectively. A total of 204 patients fit 4 ROX trajectories. In the subphenotypes of RR, when compared with group 4, the odds ratios (ORs) and 95% confidence intervals (CIs) of group 3 were 2.74 (1.48-5.07) (P = 0.001). Regarding the HR subphenotypes, in comparison to group 1, the ORs and 95% CIs were 2.20 (1.19-4.08) (P = 0.012) for group 2, 2.70 (1.40-5.23) (P = 0.003) for group 3, 2.16 (1.04-4.49) (P = 0.040) for group 5. Low last ROX had a higher mortality risk (P linear = 0.023, P nonlinear = 0.010). Trajectories of RR and HR improved the predictive ability for 28-day mortality (AUC increased by 2.5%, P = 0.020). CONCLUSIONS: For RR and HR, longitudinal subphenotypes are risk factors for 28-day mortality and have additional predictive enrichment, whereas the last ROX during the first 72 h of ICU stays is associated with 28-day mortality. These findings indicate that maintaining the health dynamic subphenotypes of RR and HR in the ICU and elevating static ROX after initial critical care may have potentially beneficial effects on prognosis in critically ill elderly patients with ARDS.

Risk factors for venous ulceration in patients with varicose veins of lower extremities.

The aim of this case-control study was to explore the potential risk factors for venous ulceration in patients with varicose veins of lower extremities and to establish a simplified diagnostic score model. Seventy subjects with varicose veins of lower extremities and venous ulceration were compared with 1164 controls with varicose veins of lower extremities and no history of venous ulceration. Stepwise multivariate logistic regression analysis was used to identify the risk factors for venous ulceration. The steps in developing the diagnostic score model were based on the Framingham Heart study. The area under the receiver operating characteristic curve (AUC) was calculated to assess the diagnostic ability of the diagnostic score model. Multivariate analysis showed that men, overweight, obesity, longer duration varicose veins, deep venous valve insufficiency, low lymphocyte counts, and high fibrinogen content were independently associated with an increased risk of venous ulceration. The AUC for the diagnostic score model was 0.75, which indicated good discriminatory ability. Special attention should be paid to the high-risk group of patients with lower extremity varicose veins. The diagnostic score model might be a useful screening tool for clinicians, policy makers, and patients.

Heterogeneity of financial toxicity and associated risk factors for older cancer survivors in China.

In China, older cancer survivors may show heterogeneity in financial toxicity (FT). We aimed to identify FT profiles among older Chinese cancer survivors and examine the association between FT profiles and individual characteristics. We used a latent profile analysis to categorize participants and a multinomial logistic regression to examine the associations. We identified three distinct FT profiles: high, moderate, and low. Participants aged 65-69 years, with a monthly household income ≥ 5,000 CNY and a high school education or above were more likely to be classified into the moderate than high FT profile, a monthly household income ≥ 5,000 CNY increased the likelihood of being in the low FT profile and living alone negatively affected the odds of being in the low FT profile. The findings identified heterogeneity in FT among this population, may help identify high-risk groups, and may enable early intervention.

Multicomponent prediction of 2-year mortality and amputation in patients with diabetic foot using a random survival forest model: Uric acid, alanine transaminase, urine protein and platelet as important predictors.

The current methods for the prediction of mortality and amputation for inpatients with diabetic foot (DF) use only conventional, simple variables, which limits their performance. Here, we used a random survival forest (RSF) model and multicomponent variables to improve the prediction of mortality and amputation for these patients. We performed a retrospective cohort study of 175 inpatients with DF who were recruited between 2014 and 2021. Thirty-one predictors in six categories were considered as potential covariates. Seventy percent (n = 122) of the participants were randomly selected to constitute a training set, and 30% (n = 53) were assigned to a testing set. The RSF model was used to screen appropriate variables for their value as predictors of 2-year all-cause mortality and amputation, and a multicomponent prediction model was established. Model performance was evaluated using the area under the curve (AUC) and the Hosmer-Lemeshow test. The AUCs were compared using the Delong test. Seventeen variables were selected to predict mortality and 23 were selected to predict amputation. Uric acid and alanine transaminase were the top two most useful variables for the prediction of mortality, whereas urine protein and platelet were the top variables for the prediction of amputation. The AUCs were 0.913 and 0.851 for the prediction of mortality for the training and testing sets, respectively; and the equivalent AUCs were 0.963 and 0.893 for the prediction of amputation. There were no significant differences between the AUCs for the training and testing sets for both the mortality and amputation models. These models showed a good degree of fit. Thus, the RSF model can predict mortality and amputation in inpatients with DF. This multicomponent prediction model could help clinicians consider predictors of different dimensions to effectively prevent DF from clinical outcomes .

Frailty and medical financial hardship among older adults with cancer in the United States.

Background: Little is known about the association between frailty level and medical financial hardship among older adults with cancer. This study aims to describe the prevalence of frailty and to identify its association with medical financial hardship among older cancer survivors in the United States. Methods: The National Health Interview Survey (NHIS; 2019-2020) was used to identify older cancer survivors (n = 3,919). Both the five-item (Fatigue, Resistance, Ambulation, Illnesses, and Low weight-for-height) FRAIL and the three-domain (Material, Psychological, and Behavioral) medical financial hardship questions were constructed based on the NHIS questionnaire. Multivariable logistic models were used to identify the frailty level associated with financial hardship and its intensity. Results: A total of 1,583 (40.3%) older individuals with cancer were robust, 1,421 (35.9%) were pre-frail, and 915 (23.8%) were frail. Compared with robust cancer survivors in adjusted analyses, frail cancer survivors were more likely to report issues with material domain (odds ratio (OR) = 3.19, 95%CI: 2.16-4.69; p < 0.001), psychological domain (OR = 1.47, 95%CI: 1.15-1.88; p < 0.001), or behavioral domain (ORs ranged from 2.19 to 2.90, all with p < 0.050), and greater intensities of financial hardship. Conclusion: Both pre-frail and frailty statuses are common in the elderly cancer survivor population, and frail cancer survivors are vulnerable to three-domain financial hardships as compared with robust cancer survivors. Ongoing attention to frailty highlights the healthy aging of older survivors, and efforts to targeted interventions should address geriatric vulnerabilities during cancer survivorship.

Collecting Patient Feedback as a Means of Monitoring Patient Experience and Hospital Service Quality - Learning from a Government-led Initiative.

Purpose: Patient feedback plays a significant role in hospital service improvement. However, how to encourage patient feedback that can guide hospital service improvement is still being explored. By examining patient feedback data related to a tertiary hospital in China that was collected from the "12345" Government Service Convenience Hotline (GSCH), the paper discusses the learnings from GSCH in encouraging patient feedback and how quality improvement initiatives have effected the number and types of complaints made by patients and their families via GSCH. Methods: The study retrospectively collected and analyzed complaints on a Tertiary General University-affiliated hospital made via GSCH between 2016 and 2020. Patient care process-related complaints were coded using the health care complaint analysis tool (HCAT) and other complaint data were categorized based on the nature of the complaints. The autoregressive integrated moving average (ARIMA) models and mosaic plots were used to observe complaints trends and different complaint variables, respectively. The relationship between various quality improvement initiatives introduced since 2018 and patient complaints was also tested. Results: Close to 67% (n=2688) of calls made to the GSCH hotlines about the hospital were classified as a complaint including 60.6% vs 39.4% related to patient care process and nonpatient care process, respectively. For patient care process-related complaints, specifically against departments and personnel, 57.72% (n=961) were on clinical departments and 55.87% (n=471) were on doctors. Comparing the proportion of the complaint data in different categories in the two-year period of 2017-2018 and 2019-2020, an increase in management problems (47.73% vs 58.50%, P<0.001) and decrease in relationship problems (33.65% vs 25.69%, P=0.002) were recorded. Conclusion: A unified, transparent, and impartial GSCH platform greatly encourages feedback from patients and families. Feedbacks provide evidence to guide health care organizations in improving the overall experience of patients and the quality of services that they provide.

Association between cold spells and serum lipid levels among the elders: a distributed-lagged effects analysis.

Little evidence about the effects of cold spells on serum lipid levels is available. The aim of this study was to explore the association between cold spells and serum lipid levels among the elders in Jinan, China. Data of old adults from health check-up program in Shandong Provincial Qianfoshan Hospital was collected for this study. Linear mixed models combined with distributed lag nonlinear models were used to examine the relationship between cold spells and serum lipid levels, considering the confounding effects of age, sex, blood pressure, body mass index, and other meteorological factors. Subgroup analysis by gender and analysis based on different definitions of cold spells were also conducted. Increased TG levels in lag 0-lag 2 days and decreased TG levels in lag 5-lag 8 days after cold spells were observed among the elders. The largest increase was 0.363 mmol/L (95% CI: 0.184 ~ 0.543) in lag 0 day, while the largest decreased TG levels was 0.083 mmol/L (95% CI: 0.147 ~ 0.019) in lag 6 day. Similar results were obtained in the analysis of different sex and based on different definitions of cold spells. However, no significant association was found between cold spells with TC, LDL-C, and HDL-C. This study indicates that cold spells were significantly associated with serum TG levels in the elders. Effective preventive measures should be implemented around the cold spells to reduce the volatility of serum lipid levels and the occurrence of subsequent cardiovascular diseases.

The incidence and risk factors analysis of acute kidney injury in hospitalized patients received diuretics: A single-center retrospective study.

Diuretics have been one of the well-known nephrotoxic drugs which can lead to acute kidney injury (AKI). However, there are few real-world studies on the incidence of AKI in hospitalized patients received diuretics. In the present study, a single-center retrospective study was conducted in our center. The clinical data of hospitalized patients received diuretics from January 2018 to December 2020 was retrospectively analyzed. Among the 18,148 hospitalized patients included in the study, 2,589 patients (14.26%) were judged as incidence with AKI, while only 252 patients were diagnosed with AKI in the medical record. Among diuretics drugs in the study, the incidence rate of AKI with torasemide was the highest with 21.62%, and hydrochlorothiazide had the lowest incidence rate (6.80%). The multiple logistic regression analysis suggested that complicated with hypertension, anemia, pneumonia, shock, sepsis, heart failure, neoplastic diseases, combined use of proton pump inhibitors (PPI) were independent risk factors for AKI related to diuretics. The logic regression models for diuretics related AKI were developed based on the included data. The model for diuretics-AKI achieved the area under the receiver operating characteristic curves (AUC) with 0.79 on 10-fold cross validation. It is urgent to improve the understanding and attention of AKI in patients received diuretics for medical workers, and the assessment of risk factors before the use of diuretics should be contributed to the early prevention, diagnosis and treatment of AKI, and ultimately reducing morbidity and improving prognosis.

Disability and the risk of subsequent mortality in elderly: a 12-year longitudinal population-based study.

BACKGROUND: Assessment the impact of disability on mortality among the elderly is vital to healthy ageing. The present study aimed to assess the long-term influence of disability on death in the elderly based on a longitudinal study. METHOD: This study used the Chinese Longitudinal Healthy Longevity Study (CLHLS) data from 2002 to 2014, including 13,666 participants aged 65 years and older in analyses. The Katz ADL index was used to assess disability status and levels. Cumulative mortality rates were estimated by the Kaplan-Meier method. Cox proportional hazards models were conducted to estimate associations between disability and all-cause mortality for overall participants, two age groups as well as specific chronic disease groups. All reported results were adjusted by survey weights to account for the complex survey design. RESULTS: During the 12-year follow-up, the death density was 6.01 per 100 person-years. The 3-years' cumulative mortality rate of nondisabled elderly was 11.9% (95%CI: 10.9, 12.9%). As the level of disability increased, the cumulative mortality rate was from 28.1% (95%CI: 23.0, 33.1%) to 77.6% (95%CI: 63.8, 91.4%). Compared with non-disabled elderly, the multiple-adjusted hazard ratio of death due to disability was 1.68 (95% CI: 1.48, 1.90). The hazard ratios varied from 1.44 (95%CI: 1.23, 1.67) to 4.45 (95%CI: 2.69, 7.38) after classifying the disability levels. The hazard ratios of death in the young-old group (65-79 years) were higher than the old-old group (80 years and over) in both level B (HR = 1.58, 95%CI: 1.25, 2.00 vs. HR = 1.22, 95%CI: 1.06, 1.39, P = 0.029) and level G (HR = 24.09, 95%CI: 10.83, 53.60 vs. HR = 2.56, 95%CI: 1.75, 3.74, P < 0.001). For patients with hypertension, diabetes, heart disease, cerebrovascular disease as well as dementia, disability increases their relative risk of mortality by 1.64 (95%CI: 1.40, 1.93), 2.85 (95%CI: 1.46, 5.58), 1.45 (95%CI: 1.02, 2.05), 2.13 (95%CI: 1.54, 2.93) and 3.56 (95%CI: 1.22, 10.38) times, respectively. CONCLUSIONS: Disability increases the risk of all-cause death in the elderly, especially those with chronic diseases and the young-old group. Further studies are needed to better understand how to effectively prevent disability in the older population.

Time series decomposition into dyslipidemia prevalence among urban Chinese population: secular and seasonal trends.

BACKGROUND: Previous epidemiological studies have indicated the seasonal variability of serum lipid levels. However, little research has explicitly examined the separate secular and seasonal trends of dyslipidemia. The present study aimed to identify secular and seasonal trends for the prevalence of dyslipidemia and the 4 clinical classifications among the urban Chinese population by time series decomposition. METHODS: A total of 306,335 participants with metabolic-related indicators from January 2011 to December 2017 were recruited based on routine health check-up systems. Multivariate direct standardization was used to eliminate uneven distributions of the age, sex, and BMI of participants over time. Seasonal and trend decomposition using LOESS (STL decomposition) was performed to break dyslipidemia prevalence down into trend component, seasonal component and remainder component. RESULTS: A total of 21.52 % of participants were diagnosed with dyslipidemia, and significant differences in dyslipidemia and the 4 clinical classifications were observed by sex (P <0.001). The secular trends of dyslipidemia prevalence fluctuated in 2011-2017 with the lowest point in September 2016. The dyslipidemia prevalence from January to March and May to July was higher than the annual average (λ = 1.00, 1.16, 1.06, 1.01, 1.02, 1.03), with the highest point in February. Different seasonal trends were observed among the 4 clinical classifications. Compared to females, a higher point was observed among males in February, which was similar to participants aged < 55 years (vs. ≥ 55 years) and participants with a BMI ≤ 23.9 (vs. BMI > 23.9). CONCLUSIONS: There were significant secular and seasonal features for dyslipidemia prevalence among the urban Chinese population. Different seasonal trends were found in the 4 clinical classifications of dyslipidemia. Precautionary measures should be implemented to control elevated dyslipidemia prevalence in specific seasons, especially in the winter and during traditional holidays.

Effect of ambient temperatures on category C notifiable infectious diarrhea in China: An analysis of national surveillance data.

BACKGROUND: Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions. METHODS: Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature. RESULTS: A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier. CONCLUSIONS: The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.

Financial hardship in Chinese cancer survivors.

BACKGROUND: The purpose of this study was to estimate the proportion of Chinese cancer survivors experiencing financial hardship and then examine the relationship between material and behavioral financial hardship. METHODS: This study surveyed 964 cancer survivors who were 30 to 64 years old and 644 survivors who were 65 years old or older during 2015-2016 (1608 survivors in all). Material financial hardship was measured by whether they had borrowed money because of cancer, its treatment, or the lasting effects of treatment, and behavioral financial hardship was measured by whether they had forgone some cancer-related medical care because of cost. Multivariable logistic regression models were used to examine factors associated with material financial hardship by age group. RESULTS: Approximately 44% of the cancer survivors who were 65 years old or older borrowed money or went into debt because of cancer, and 54% of younger patients (P < .01) reported cancer-related debts. Among these survivors with cancer care debt, survivors aged 65 years old or older had a lower proportion of borrowing more than 50,000 Chinese yuan (CNY; approximately US $7700) than survivors aged 30 to 64 years (14% vs 20%). In both age groups, approximately 10% of cancer survivors reported that they had experienced behavioral financial hardship. After adjustments for covariates, cancer survivors who reported material financial problems were more likely to report behavioral financial hardship (odds ratio [OR] for those aged 30-64 years, 3.72; 95% confidence interval [CI], 2.13-6.50; OR for those aged 65 years or older, 5.48; 95% CI, 2.69-11.15). CONCLUSIONS: Older cancer survivors in China experience significant material financial hardship, but it is not as noticeable as younger patients' hardship. The results highlight the importance of identifying cancer survivors who are more likely to experience financial hardship and improving the affordability of cancer care in China.

Effects and interaction of meteorological factors on influenza: Based on the surveillance data in Shaoyang, China.

BACKGROUND: Previous studies have demonstrated that meteorological factors influence the incidence of influenza. However, little is known regarding the interactions of meteorological factors on the risk of influenza in China. OBJECTIVE: The study aimed to evaluate the associations between meteorological factors and influenza in Shaoyang of southern China, and explore the interaction of temperature with humidity and rainfall. METHODS: Weekly meteorological data and disease surveillance data of influenza in Shaoyang were collected from 2009 to 2012. According to the incubation period and infectious period of influenza virus, the maximum lag period was set as 3 weeks. A generalized additive model was conducted to evaluate the effect of meteorological factors on the weekly number of influenza cases and a stratification model was applied to investigate the interaction. RESULTS: During the study period, the total number of influenza cases that were notified in the study area was 2506, with peak times occurring from December to March. After controlling for the confounders, each 5 °C decrease in minimum temperature was related to 8% (95%CI: 1-15%) increase in the number of influenza cases at a 1-week lag. There was an interaction between minimum temperature and relative humidity and the risk of influenza was higher in cold and less humid conditions than other conditions. The interaction between minimum temperature and rainfall was not statistically significant in our study. CONCLUSIONS: The study suggests that minimum temperature is inversely associated with influenza in the study area of China, and the effect can be modified by relative humidity. Meteorological variables could be integrated in current public health surveillance system to better prepare for the risks of influenza.

Identifying different types of flood-sensitive diarrheal diseases from 2006 to 2010 in Guangxi, China.

Floods may influence different types of diarrheal diseases and epidemiological studies of pathogen-specific diarrhea due to floods in China are still needed. In addition, few studies have been conducted to quantify the lag and cumulative risk of diarrheal disease due to floods in Guangxi, China. Our study aimed to identify different types of diarrheal diseases that were sensitive to floods and to quantify their lag and cumulative impact. A matched analysis based on time series data of floods and infectious disease from 2006 to 2010 was conducted in Guangxi, China. Each flood day was treated as an independent unit in our study. A simplified assumption that each day of the flood confers the same risk was adopted before analysis. Each flood day was matched to a non-flood day by city and time. Log-linear mixed-effects regression models were used to quantify the association between different types of diarrheal diseases and floods. Lag and cumulative effects were also calculated to get delayed and overall effects. A total of 45,131 diarrhea cases were notified in the study area over the study period. After controlling for the long-term trend, seasonality, and meteorological factors, floods caused a significantly increased risk of total diarrheal diseases. The RR was highest at lag 2 days (RR=1.24, 95% CI: 1.11-1.40). Floods caused a significantly increased risk in bacillary dysentery and in other infectious diarrhea, but not in typhoid fever and paratyphoid fever. Floods were significantly associated with total diarrheal diseases and other infectious diarrhea for both cumulative lag 0-7 and 0-14 days. Our study provides strong evidence of a positive association between floods and diarrheal diseases including bacillary dysentery and other infectious diarrhea in study area. Public health interventions should be taken to prevent a potential risk of these flood-sensitive diarrheal diseases according to the different lag period after floods.

Effect of ambient temperature and its effect modifiers on bacillary dysentery in Jinan, China.

BACKGROUND: Studies about the modified effect among various meteorological factors on bacillary dysentery (BD) are limited. This study aimed to investigate the effect of ambient temperature and its effect modifiers on BD in Jinan. METHODS: Daily data of BD cases and meteorological factors from 2005 to 2013 were collected. A generalized additive model (GAM) was conducted to explore the relationship between meteorological factors and BD. Then a distributed lag non-linear model (DLNM) was developed to assess the lag and cumulative effect. Finally, the modified effect between temperature and other meteorological factors on BD was explored by the GAM and a weather-stratified model. RESULTS: A total of 11,738 cases of BD were notified over the study period. The exposure-response relationship between temperature and BD was liner with a single threshold value of 0 °C. Results of DLNM showed that after temperature exceeds the threshold, each 5 °C rise in temperature caused a 19% (RR = 1.19, 95% CI: 1.14-1.24) increase in the number of cases of BD at lag 0. The analysis of cumulative effects showed that each 5 °C rise in temperature can increase the number of cases by 61% (RR = 1.61, 95% CI: 1.58-1.63) at lag 0-lag 7 days. The effect modification of the association between temperature and BD by humidity was observed in our study, while the modification by precipitation and wind speed were not statistically significant. The risk of BD was highest when temperature and humidity were both high. CONCLUSIONS: Our study indicates that temperature is significantly associated with the risk of BD in the study area, and the effect can be modified by humidity. Public health professionals and medical service providers should pay more attention BD prevention and control when the weather condition of both high temperature and high humidity would occur.

Association between floods and typhoid fever in Yongzhou, China: Effects and vulnerable groups.

BACKGROUND: Little information about the effects of floods on typhoid fever is available in previous studies. This study aimed to examine the relationships between floods and typhoid fever and to identify the vulnerable groups in Yongzhou, China. METHODS: Weekly typhoid fever data, flood data and meteorological data during the flood season (April to September) from 2005 to 2012 were collected for this study. A Poisson generalized linear model combined with a distributed lag non-linear model was conducted to quantify the lagged and cumulative effects of floods on typhoid fever, considering the confounding effects of long-term trend, seasonality, and meteorological variables. The model was also used to calculate risk ratios of floods for weekly typhoid fever cases among various subpopulations. RESULTS: After adjusting for long-term trend, seasonality, and meteorological variables, floods were associated with an increased number of typhoid fever cases with a risk ratio of 1.46 (95% CI: 1.10-1.92) at 1-week lag and a cumulative risk ratio of 1.76 (95% CI: 1.21-2.57) at lag 0-1 weeks. Males, people aged 0-4 years old, people aged 15-64 years old, farmers, and children appeared to be more vulnerable than the others. CONCLUSIONS: Our study indicates that floods could significantly increase the risks of typhoid fever with lag effects of 1 week in the study areas. Precautionary measures should be taken with a focus on the identified vulnerable groups in order to control the transmission of typhoid fever associated with floods.