Cumulative Relative Risk Research Articles

Short-term associations of diarrhoeal diseases in children with temperature and precipitation in seven low- and middle-income countries from Sub-Saharan Africa and South Asia in the Global Enteric Multicenter Study.

Diarrhoeal diseases cause a heavy burden in developing countries. Although studies have described the seasonality of diarrhoeal diseases, the association of weather variables with diarrhoeal diseases has not been well characterized in resource-limited settings where the burden remains high. We examined short-term associations between ambient temperature, precipitation and hospital visits due to diarrhoea among children in seven low- and middle-income countries. Hospital visits due to diarrhoeal diseases under 5 years old were collected from seven sites in The Gambia, Mali, Mozambique, Kenya, India, Bangladesh, and Pakistan via the Global Enteric Multicenter Study from December 2007 to March 2011. Daily weather data during the same period were downloaded from the ERA5-Land. We fitted time-series regression models to examine the relationships of daily diarrhoea cases with daily ambient temperature and precipitation. Then, we used meta-analytic tools to examine the heterogeneity between the site-specific estimates. The cumulative relative risk (RR) of diarrhoea for temperature exposure (95th percentile vs. 1st percentile) ranged from 0.24 to 8.07, with Mozambique and Bangladesh showing positive associations, while Mali and Pakistan showed negative associations. The RR for precipitation (95th percentile vs. 1st percentile) ranged from 0.77 to 1.55, with Mali and India showing positive associations, while the only negative association was observed in Pakistan. Meta-analysis showed substantial heterogeneity in the association between temperature-diarrhoea and precipitation-diarrhoea across sites, with I2 of 84.2% and 67.5%, respectively. Child diarrhoea and weather factors have diverse and complex associations across South Asia and Sub-Saharan Africa. Diarrhoeal surveillance system settings should be conceptualized based on the observed pattern of climate change in these locations.

Lagged effects of climate factors on bacillary dysentery in western China.

Evidence has shown that the incidence of bacillary dysentery (BD) is associated with climatic factors. However, the lagged effects of climatic factors on BD are still unclear, especially lacking research evidence from arid and semi-arid regions. Therefore, this study aims to add new insights into this research field. Spatial autocorrelation, time series analysis and spatiotemporal scans were used to perform descriptive analyses of BD cases from 2009 to 2019. On the basis of monthly data from 2015 to 2019, multivariable distributed lag non-linear models were used to investigate the lagged effects of climatic factors on BD. The hot spots for BD incidence are gradually decreasing and becoming increasingly concentrated in the southern part of Gansu Province. The maximum cumulative relative risks for monthly average temperature, sunshine duration, average relative humidity and precipitation were 3.21, 1.64, 1.55 and 1.41, respectively. The lagged effects peaked either in the current month or with a 1-month lag, and the shape of the exposure-response curve changed with the increase in maximum lag time. After stratification by per capita gross domestic product, there were differences in the effects. Climatic factors can influence the incidence of BD, with effects varying across different lag times. It is imperative to vigilantly track the disparities in the incidence of BD attributable to economic factors.

Rainfall events and daily mortality across 645 global locations: two stage time series analysis

ObjectiveTo examine the associations between characteristics of daily rainfall (intensity, duration, and frequency) and all cause, cardiovascular, and respiratory mortality.DesignTwo stage time series analysis.Setting645 locations across 34 countries or regions.PopulationDaily...

Association between compound extreme weather event types and the spectrum of emergency ambulance calls: A metropolitan study in Shenzhen

Compound extreme weather events, a combination of weather and climate drivers that lead to potentially high-impact events, are becoming more frequent with climate change. The number of emergency ambulance calls (EACs) is expected to increase during compound extreme weather events. However, the extent of these increases and the trends over time have not been fully assessed. We obtained 242,165 EAC records for Shenzhen from January 1, 2020, to June 30, 2023. A compound extreme weather event was defined as the occurrence of at least two extreme weather events on the same day. A distributed lag non-linear model was used to explore the exposure-response and lag-response relationships between various compound extreme weather events and all-cause and specific-cause EACs. Compound Cold & Strong Monsoon events had more significant impacts on EACs for all causes and endocrine diseases, with the cumulative relative risk (CRR) of 1.401 (95% confidence interval (CI):1.290-1.522) and 1.641 (95% CI:1.279-2.105). Compound Heat Wave & Lightning events had more obvious impacts on digestive disease and endocrine disease EACs, with the CRRs of 1.185 (95% CI:1.041-1.348) and 1.278 (95% CI:0.954-1.711), respectively. Compound Rainstorm & Lightning & Heat Wave events also led to increased RRs of EACs for all causes (CRR: 1.168, 95% CI:1.012-1.348), cardiovascular diseases (CRR: 1.221, 95% CI:0.917-1.624), digestive diseases (CRR: 1.395, 95% CI:1.130-1.721), and endocrine diseases (CRR: 1.972, 95% CI:1.235-3.149). There was no increased RR in the compound Rainstorm & Lightning events for all types of EACs. Our study explored the relationship between EACs and compound extreme weather events, suggesting that compound extreme weather events are associated with the acute onset of cardiovascular diseases, digestive diseases, and endocrine diseases, increasing the burden on emergency ambulance resources for both all causes and specific diseases mentioned above.

Characterizing the seasonal influenza disease burden attributable to climate variability: A nationwide time-series modelling study in Japan, 2000−2019

BackgroundAmbient temperature and humidity are established environmental stressors with regard to influenza infections; however, mapping disease burden is difficult owing to the complexities of the underlying associations and differences in vulnerable population distributions. In this study, we aimed to quantify the burden of influenza attributable to non-optimal ambient temperature and absolute humidity in Japan considering geographical differences in vulnerability. MethodsThe exposure−lag−response relationships between influenza incidence, ambient temperature, and absolute humidity in all 47 Japanese prefectures for 2000−2019 were quantified using a distributed lag non-linear model for each prefecture; the estimates from all the prefectures were then pooled using a multivariate mixed-effects meta-regression model to derive nationwide average associations. Association between prefecture-specific indicators and the risk were also examined. Attributable risks were estimated for non-optimal ambient temperature and absolute humidity according to the exposure−lag−response relationships obtained before. ResultsA total of 25,596,525 influenza cases were reported during the study period. Cold and dry conditions significantly increased influenza incidence risk. Compared with the minimum incidence weekly mean ambient temperature (29.8 °C) and the minimum incidence weekly mean absolute humidity (20.2 g/m3), the cumulative relative risks (RRs) of influenza in cold (2.5 °C) and dry (3.6 g/m3) conditions were 2.79 (95% confidence interval [CI]: 1.78−4.37) and 3.20 (95% CI: 2.37−4.31), respectively. The higher RRs for cold and dry conditions were associated with geographical and climatic indicators corresponding to the central and northern prefectures; demographic, socioeconomic, and health resources indicators showed no clear trends. Finally, 27.25% (95% empirical CI [eCI]: 5.54−36.35) and 32.35% (95% eCI: 22.39−37.87) of all cases were attributable to non-optimal ambient temperature and absolute humidity (6,976,300 [95% eCI: 1,420,068−9,306,128] and 8,280,981 [95% eCI: 8,280,981−9,693,532] cases), respectively. ConclusionsThese findings could help identify the most vulnerable populations in Japan and design adaptation policies to reduce the attributable burden of influenza due to climate variability.

Efficacy and Safety of Standard Triple Therapy for Helicobacter pylori Eradication in Latin America: A Systematic Review and Meta-Analysis.

To evaluate the efficacy and safety of standard triple therapy (STT) in Latin America. Helicobacter pylori infection affects more than 50% of the Latin Americans and leads to gastric mucosa damage. Scarce data on effective therapeutic approaches in the region underscores the need for comprehensive information. The analysis included Randomized Controlled Trials published up to the year 2020, comparing STT with other treatments. Cumulative relative risks (RR) were estimated, with 95% CI, according to intention-to-treat (ITT) and per protocol (PP) analysis. Eleven studies (clinical trials conducted between 1995 and 2013), revealed cumulative eradication rates of 78.31-90.63% (ITT) and 76.71-93.55% (PP). The eradication with the STT was superior to sequential therapy (ITT-RR: 10.6, 95% CI: 1.01 to 1.12) (PP-RR: 10.6, 95% CI: 1.02-1.11) and dual therapy (ITT-RR: 1.61, 95% CI: 1.13-2.30) (PP-RR: 1.72, 95% CI: 1.25-2.37), but is less effective than other triple therapies (PP-RR: 0.85, 95% CI: 0.78-092). Regarding adverse effects, diarrhea, metallic taste, nausea, vomiting, and headache were the most common symptoms across treatments. Abdominal pain was associated with STT (ITT-RR: 1.75, 95% CI: 1.07-2.86). STT was a safe regimen but with acceptable efficacy (most eradication rates <90%). Due to rising clarithromycin resistance, the study suggests avoiding STT as a first-line treatment. These results must be considered with caution due to the low representativeness of several Latin American countries and the lack of recent high-quality randomized studies.

Risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 over 2017-2022 in Sanandaj, an area of Iran.

The risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 has been less investigated. In this study, the attributable risk was estimated in an area of Iran. The predicted air PM2.5 using satellite data and a two-stage regression model was used as the predictor of the diseases. The dose-response linkage between the bias-corrected predictor employing a strong statistical approach and the outcomes was evaluated using the distributed lag nonlinear model. We considered two distinct scenarios of PM2.5 for the risk estimation. Alongside the risk, the attributable risk and number were estimated for different levels of PM2.5 by age and gender categories. The cumulative influence of PM2.5 particles on respiratory illnesses was statistically significant at 13-16µg/m3 relative to the reference value (median), mostly apparent in the middle delays. The cumulative relative risk of 90th and 95th percentiles were 2.03 (CI 95%: 1.28, 3.19) and 2.25 (CI 95%: 1.28, 3.96), respectively. Nearly 600 cases of the diseases were attributable to the non-optimum values of the pollutant during 2017-2022, of which more than 400 cases were attributed to high values range. The predictor's influence on cardiovascular illnesses was along with uncertainty, indicating that additional research into their relationship is needed. The bias-corrected PM2.5 played an essential role in the prediction of respiratory illnesses, and it may likely be employed as a trigger for a preventative strategy.

Association of ambient temperature on acute ischemic stroke in Yancheng, China

BackgroundAcute ischemic stroke (AIS) is a major global public health issue. There is limited research on the relationship between ambient temperature and AIS hospital admissions, and the results are controversial. Our objective is to assess the short-term impact of ambient temperature on the risk of AIS hospital admissions in Yancheng, China.MethodsWe collected data on daily AIS hospital admissions, meteorological factors, and air quality in Yancheng from 2014 to 2019. We used Poisson regression to fit generalized linear models and distributed lag non-linear models to explore the association between ambient temperature and AIS hospital admissions. The effects of these associations were evaluated by stratified analysis by sex and age.ResultsFrom 2014 to 2019, we identified a total of 13,391 AIS hospital admissions. We observed that the influence of extreme cold and heat on admissions for AIS manifests immediately on the day of exposure and continues for a duration of 3–5 days. Compared to the optimal temperature (24.4 °C), the cumulative relative risk under extreme cold temperature (-1.3 °C) conditions with a lag of 0–5 days was 1.88 (95%CI: 1.28, 2.78), and under extreme heat temperature (30.5 °C) conditions with a lag of 0–5 days was 1.48 (95%CI: 1.26, 1.73).ConclusionsThere is a non-linear association between ambient temperature and AIS hospital admission risk in Yancheng, China. Women and older patients are more vulnerable to non-optimal temperatures. Our findings may reveal the potential impact of climate change on the risk of AIS hospital admissions.

Emergency room visits (ERVs) among occupational groups associated with ambient conditions in Taiwan.

This population-based study explored emergency room visits (ERVs) from all-causes, circulatory and respiratory diseases among different occupational groups in Taiwan associated with ambient average temperature. Daily area-age-sex specific ERVs records were obtained from the Taiwan's Ministry of Health and Welfare from 2009 to 2018. Distributed lag-nonlinear model (DLNM) was used to estimate the exposure-response relationships between daily average temperature and ERVs for all-causes, circulatory and respiratory diseases by occupational groups. Random-effects meta-analysis was used to pool the overall cumulative relative risk (RR) and 95% confidence interval (CI). The exposure-response curves showed ERVs of all-cause and respiratory diseases increased with rising temperature across all occupational groups. These effects were consistently stronger among younger (20-64 years old) and outdoor workers. In contrast, ERVs risk from circulatory diseases increased significantly during cold snaps, with a substantially higher risk for female workers. Interestingly, female workers, regardless of indoor or outdoor work, consistently showed a higher risk of respiratory ERVs during hot weather compared to males. Younger workers (20-64 years old) exhibited a higher risk of ERVs, likely due to job profiles with greater exposure to extreme temperatures. Notably, the highest risk of all-causes ERVs was observed in outdoor male laborers (union members), followed by farmers and private employees, with the lowest risk among indoor workers. Conversely, female indoor workers and female farmers faced the highest risk of respiratory ERVs. Again, female farmers with consistent outdoor exposure had the highest risk of circulatory ERVs during cold conditions. Our findings highlighted the complexity of temperature-related health risks associated with different occupational contexts. The population-level insights into vulnerable occupational groups could provide valuable comprehension for policymakers and healthcare practitioners.

Meteorological parameters and hospital-acquired falls—A multicenter retrospective study based on 10 years of adverse events reporting system data

Objective and rationaleHospital-acquired falls are common and serious adverse events in medical institutions, with high incidence and injury rates. Studying the occurrence patterns of hospital-acquired falls is important for preventing falls in hospitalized patients. However, the effect of meteorological factors on hospital-acquired falls has not been elucidated. Therefore, this study explored the impact of meteorological parameters on hospital-acquired falls in Chongqing, China, and provided new ideas for the clinical prevention of falls in patients. MethodsCorrelation analysis and distributed lag nonlinear models were employed to analyze the relationship between 3890 cases of hospital-acquired falls and meteorological data in 13 hospitals in 11 districts and counties in Chongqing from January 2013 to April 2023. ResultsThe number of hospital-acquired falls demonstrated a nonlinear correlation with the daily average relative humidity and negatively correlated with sunshine duration; however, temperature, air pressure, and wind speed were not correlated. Compared to the reference humidity (87 %), the immediate effects of daily average relative humidity (65–68 % and 90–97 %) increased the risk of hospital-acquired falls on the same day (relative risk [RR]:1.027–1.243). When the daily average relative humidity was 95–97 %, lags of 0–1 d and 8–12 d had greater effects on falls (RR:1.073–1.243). The daily average relative humidities of 62–74 % and 91–97 % were statistically significant at cumulative relative risk (CRR)of 4, 7, 10, and 14 d with a cumulative lag (CRR: 1.111–4.277). On sex and age stratification, the lag and cumulative effects of relative humidity more significantly impacted falls in women and patients aged ≥65 years. ConclusionDaily average relative humidity had a nonlinear correlation and lag effect on hospital-acquired falls; therefore, medical institutions should pay attention to the effect of relative humidity on hospital-acquired falls in patients, especially old and female patients.

The effect of ambient temperatures on hospital admissions for kidney diseases in Central Australia

This study aimed to quantify risk of hospitalisations for kidney diseases related to ambient temperature in Central Australia, Northern Territory (NT).Daily hospitalisation data were extracted for Alice Springs Hospital, Central Australia, 2010–2021. The association between daily mean temperature and daily hospital admissions for total kidney and specific kidney conditions was assessed using a quasi-Poisson Generalized Linear Model combined with a distributed lag non-linear model.A total of 52,057 hospitalisations associated with kidney diseases were recorded. In general, risk of specific kidney related hospitalisations was immediate due to hot temperatures and prolonged due to cold temperatures. Relative to the minimum-risk temperature (5.1 °C), at 31 °C, cumulative relative risk (RR) of hospitalisations for total kidney disease (TKD) was 1.297 [95% CI 1.164,1.446] over lag0-1 days, for chronic kidney disease (CKD) cumulative RR was 1.269 [95% CI 1.115,1.444] and for kidney failure (KF) cumulative RR was 1.252 [95% CI 1.107,1.416] at lag 0, and for urinary tract infection (UTI) cumulative RR was 1.522 [95% CI 1.072,2.162] over lag0-7 days. At 16 °C and over lag0-7 days, cumulative RR of hospitalisations for TKD was 1.320 [95% CI 1.135,1.535], for CKD was 1.232 [95% CI 1.025,1.482], for RF was 1.233 [95% CI 1.035,1.470] and for UTI was 1.597 [95% CI 1.143, 2.231]. Both cold and hot temperatures were also associated with increased risks of kidney related total hospitalisations among First Nations Australians and women. Overall, temperature attributable to 13.7% (i.e. 7138 cases) of kidney related hospitalisations with higher attributable hospitalisations from cold temperature.Given the significant burden of kidney disease and projected increases in extreme temperatures associated with climate change in NT including Central Australia there is a need to implement public health and environmental health risk reduction strategies and awareness programs to mitigate potential adverse health effects of extreme temperatures.

The effects of meteorological factors and air pollutants on the incidence of tuberculosis in people living with HIV/AIDS in subtropical Guangxi, China.

Previous studies have shown the association between tuberculosis (TB) and meteorological factors/air pollutants. However, little information is available for people living with HIV/AIDS (PLWHA), who are highly susceptible to TB. Data regarding TB cases in PLWHA from 2014 to2020 were collected from the HIV antiviral therapy cohort in Guangxi, China. Meteorological and air pollutants data for the same period were obtained from the China Meteorological Science Data Sharing Service Network and Department of Ecology and Environment of Guangxi. A distribution lag non-linear model (DLNM) was used to evaluate the effects of meteorological factors and air pollutant exposure on the risk of TB in PLWHA. A total of 2087 new or re-active TB cases were collected, which had a significant seasonal and periodic distribution. Compared with the median values, the maximum cumulative relative risk (RR) for TB in PLWHA was 0.663 (95% confidence interval [CI]: 0.507-0.866, lag 4 weeks) for a 5-unit increase in temperature, and 1.478 (95% CI: 1.116-1.957, lag 4 weeks) for a 2-unit increase in precipitation. However, neither wind speed nor PM10 had a significant cumulative lag effect. Extreme analysis demonstrated that the hot effect (RR = 0.638, 95%CI: 0.425-0.958, lag 4 weeks), the rainy effect (RR = 0.285, 95%CI: 0.135-0.599, lag 4 weeks), and the rainless effect (RR = 0.552, 95%CI: 0.322-0.947, lag 4 weeks) reduced the risk of TB. Furthermore, in the CD4(+) T cells < 200 cells/µL subgroup, temperature, precipitation, and PM10 had a significant hysteretic effect on TB incidence, while temperature and precipitation had a significant cumulative lag effect. However, these effects were not observed in the CD4(+) T cells ≥ 200 cells/µL subgroup. For PLWHA in subtropical Guangxi, temperature and precipitation had a significant cumulative effect on TB incidence among PLWHA, while air pollutants had little effect. Moreover, the influence of meteorological factors on the incidence of TB also depends on the immune status of PLWHA.

Private vs. public emergency visits for mental health due to heat: An indirect socioeconomic assessment of heat vulnerability and healthcare access, in Curitiba, Brazil

Few studies have explored the influence of socioeconomic status (SES) on the heat vulnerability of mental health (MH) patients. As individual socioeconomic data was unavailable, we aimed to fill this gap by using the healthcare system type as a proxy for SES. Brazilian national statistics indicate that public patients have lower SES than private. Therefore, we compared the risk of emergency department visits (EDVs) for MH between patients from both healthcare types. EDVs for MH disorders from all nine public (101,452 visits) and one large private facility (154,954) in Curitiba were assessed (2017–2021). Daily mean temperature was gathered and weighed from 3 stations. Distributed-lag non-linear model with quasi-Poisson (maximum 10-lags) was used to assess the risk. We stratified by private and public, age, and gender under moderate and extreme heat. Additionally, we calculated the attributable fraction (AF), which translates individual risks into population-representative burdens – especially useful for public policies. Random-effects meta-regression pooled the risk estimates between healthcare systems. Public patients showed significant risks immediately as temperatures started to increase. Their cumulative relative risk (RR) of MH-EDV was 7.5 % higher than the private patients (Q-Test 26.2 %) under moderate heat, suggesting their particular heat vulnerability. Differently, private patients showed significant risks only under extreme heat, when their RR became 4.3 % higher than public (Q-Test 6.2 %). These findings suggest that private patients have a relatively greater adaptation capacity to heat. However, when faced with extreme heat, their current adaptation means were potentially insufficient, so they needed and could access healthcare freely, unlike their public counterparts. MH patients would benefit from measures to reduce heat vulnerability and access barriers, increasing equity between the healthcare systems in Brazil. AF of EDVs due to extreme heat was 0.33 % (95%CI 0.16;0.50) for the total sample (859 EDVs). This corroborates that such broad population-level policies are urgently needed as climate change progresses.

Association between synoptic types in Beijing and acute myocardial infarction hospitalizations: A comprehensive analysis of environmental factors

BackgroundEnvironmental factors like air pollution and temperature can trigger acute myocardial infarction (AMI). However, the link between large-scale weather patterns (synoptic types) and AMI admissions has not been extensively studied. This research aimed to identify the different synoptic air types in Beijing and investigate their association with AMI occurrences. MethodsWe analyzed data from Beijing between 2013 and 2019, encompassing 2556 days and 149,632 AMI cases. Using principal component analysis and hierarchical clustering, classification into distinct synoptic types was conducted based on weather and pollution measurements. To assess the impact of each type on AMI risk over 14 days, we employed a distributed lag non-linear model (DLNM), with the reference being the lowest risk type (Type 2). ResultsFour synoptic types were identified: Type 1 with warm, humid weather; Type 2 with warm temperatures, low humidity, and long sunshine duration; Type 3 with cold weather and heavy air pollution; and Type 4 with cold temperatures, dryness, and high wind speed. Type 4 exhibited the greatest cumulative relative risk (CRR) of 1.241 (95%CI: 1.150, 1.339) over 14 days. Significant effects of Types 1, 3, and 4 on AMI events were observed at varying lags: 4–12 days for Type 1, 1–6 days for Type 3, and 1–11 days for Type 4. Females were more susceptible to Types 1 and 3, while individuals younger than 65 years old showed increased vulnerability to Types 3 and 4. ConclusionAmong the four synoptic types identified in Beijing from 2013 to 2019, Type 4 (cold, dry, and windy) presented the highest risk for AMI hospitalizations. This risk was particularly pronounced for males and people under 65. Our findings collectively highlight the need for improved methods to identify synoptic types. Additionally, developing a warning system based on these synoptic conditions could be crucial for prevention.

Association between ambient temperature and genitourinary emergency ambulance dispatches in Japan: A nationwide case-crossover study.

Although the effects of temperature on genitourinary morbidity and mortality have been investigated in several countries, it remains largely unexplored in Japan. We investigated the association between ambient temperature and genitourinary emergency ambulance dispatches (EADs) in Japan and the modifying roles of sex, age, and illness severity. We conducted a time-stratified case-crossover study with conditional quasi-Poisson regression to estimate the association between mean temperature and genitourinary EADs in all prefectures of Japan between 2015 and 2019. A mixed-effects meta-analysis was used to pool the association at the country level. Subgroup analyses were performed to explore differences in associations stratified by sex, age, and illness severity. We found an increased risk of genitourinary EAD associated with higher temperatures. The cumulative relative risk (RR) at the 99th temperature percentile compared with that at the 1st percentile was 1.74 (95% confidence interval (CI) = [1.60, 1.89]). We observed higher heat-related RRs in males (RR = 1.89; 95% CI = [1.73, 2.07]) than females (RR = 1.56; 95% CI = [1.37, 1.76]), and in the younger (RR = 2.13; 95% CI = [1.86, 2.45]) than elderly (RR = 1.39; 95% CI = [1.22, 1.58]). We found a significant association for those with mild or moderate cases (RR = 1.77; 95% CI = [1.62, 1.93]), but not for severe or life-threatening cases (RR = 1.20; 95% CI = [0.80, 1.82]). Our study revealed heat effects on genitourinary EADs in Japan. Men, youth, and mild-moderate illnesses were particularly vulnerable subgroups. These findings underscore the need for preventative measures aimed at mitigating the impact of temperature on genitourinary emergencies.

The one-year infection risk among patients diagnosed with giant cell arteritis: use of antibiotics and hospitalisations

Abstract Objectives Patients with giant cell arteritis (GCA) primarily have their infections managed by primary care providers and hospitalisation is rarely necessary. Existing studies in GCA focus on infection-related hospitalisations only, whereas the use of antibiotic prescriptions is largely unknown. This study aims to examine the one-year overall infection risk among patients with GCA. Methods This nationwide observational cohort study included patients aged ≥50 years with a first-time GCA diagnosis in the Danish National Patient Registry (1996–2022). Patients with GCA were matched 1:10 by sex and date of birth with general population individuals and followed from date of diagnosis. Overall infections were defined as redeemed antibiotic prescriptions or infection-related hospitalisations. Utilising a pseudo-observation approach, we assessed 1-year cumulative incidence proportions (CIP), risk differences (RD) and relative risks (RR) of infections. Results The study included 17 773 incident patients with GCA and 177 730 reference individuals. Patients with GCA had a 1-year CIP of 52.4% (95% CI: 51.7–53.2) for overall infections and 17.6% (95% CI: 17.1–18.2) for infection-related hospitalisations. Compared with the reference cohort, patients with GCA had a RR of 1.40 (95% CI: 1.38–1.42) for overall infections and 2.71 (95% CI: 2.61–2.82) for infection-related hospitalisations. Additionally, higher cumulative glucocorticoid doses, advanced age (≥70 years) and higher comorbidity were associated with an increased risk of infections among patients with GCA. Conclusions The use of antibiotic prescriptions and infection-related hospitalisations in the first year after a GCA diagnosis is high compared with the background population. The cumulative glucocorticoid dose is associated with the infection risk.

Associations between short-term exposure to ambient temperature and renal disease mortality in Japan during 1979-2019: A time-stratified case-crossover analysis.

Previous studies have indicated that renal disease mortality is sensitive to ambient temperatures. However, most have been limited to the summer season with inconclusive evidence for changes in population vulnerability over time. This study aims to examine the association between short-term exposure to ambient temperatures and mortality due to renal diseases in Japan, and how this association varied over time. We conducted a two-stage, time-stratified case-crossover study from 1979 to 2019 across 47 prefectures of Japan. We obtained the data of daily mortality counts for all renal diseases, acute renal failure, and chronic renal disease. We fitted a conditional quasi-Poisson regression model with a distributed lag nonlinear model. A random-effects meta-analysis was applied to calculate national averages. We performed additional analyses by four subperiods, sex, and age groups. We analyzed 997,590 renal mortality cases and observed a reversed J-shaped association. Lower temperatures were associated with increased mortality in all renal disease categories. The cumulative relative risks at 2.5th percentile compared to the minimum mortality temperature percentile were 1.34 (95% confidence interval [CI] = 1.29, 1.40), 1.51 (95% CI = 1.33, 1.71), and 1.33 (95% CI = 1.24, 1.43) for all renal, acute renal failure, and chronic renal disease mortality, respectively. The associations were observed in individuals of both sexes and aged 65 years and above. The associations of kidney mortality with low temperature remained consistent, while the associations with high temperature were pronounced in the past, but not in recent periods. Protection for individuals with impaired renal function from exposure to low temperatures during cold seasons is warranted.

Temperature fluctuation and acute myocardial infarction in Beijing: an extended analysis of temperature ranges and differences.

Few studies examined the relationship between temperature fluctuation metrics and acute myocardial infarction (AMI) hospitalizations within a single cohort. We aimed to expand knowledge on two basic measures: temperature range and difference. We conducted a time-series analysis on the correlations between temperature range (TR), daily mean temperature differences (DTDmean), and daily mean-maximum/minimum temperature differences (TDmax/min) and AMI hospitalizations, using data between 2013 and 2016 in Beijing, China. The effects of TRn and DTDmeann over n-day intervals were compared, respectively. Subgroup analysis by age and sex was performed. A total of 81,029 AMI hospitalizations were included. TR1, TDmax, and TDmin were associated with AMI in J-shaped patterns. DTDmean1 was related to AMI in a U-shaped pattern. These correlations weakened for TR and DTDmean with longer exposure intervals. Extremely low (1st percentile) and high (5°C) DTDmean1 generated cumulative relative risk (CRR) of 2.73 (95% CI: 1.56-4.79) and 2.15 (95% CI: 1.54-3.01). Extremely high TR1, TDmax, and TDmin (99th percentile) correlated with CRR of 2.00 (95% CI: 1.73-2.85), 1.71 (95% CI: 1.40-2.09), and 2.73 (95% CI: 2.04-3.66), respectively. Those aged 20-64 had higher risks with large TR1, TDmax, and TDmin, while older individuals were more affected by negative DTDmean1. DTDmean1 was associated with a higher AMI risk in females. Temperature fluctuations were linked to increased AMI hospitalizations, with low-temperature extremes having a more pronounced effect. Females and the older adult were more susceptible to daily mean temperature variations, while younger individuals were more affected by larger temperature ranges.

Association between environmental factors and dengue incidence in Lao People’s Democratic Republic: a nationwide time-series study

BackgroundDengue fever is a vector-borne disease of global public health concern, with an increasing number of cases and a widening area of endemicity in recent years. Meteorological factors influence dengue transmission. This study aimed to estimate the association between meteorological factors (i.e., temperature and rainfall) and dengue incidence and the effect of altitude on this association in the Lao People’s Democratic Republic (Lao PDR).MethodsWe used weekly dengue incidence and meteorological data, including temperature and rainfall, from 18 jurisdictions in Lao PDR from 2015 to 2019. A two-stage distributed lag nonlinear model with a quasi-Poisson distribution was used to account for the nonlinear and delayed associations between dengue incidence and meteorological variables, adjusting for long-term time trends and autocorrelation.ResultsA total of 55,561 cases were reported in Lao PDR from 2015 to 2019. The cumulative relative risk for the 90th percentile of weekly mean temperature (29 °C) over 22 weeks was estimated at 4.21 (95% confidence interval: 2.00–8.84), relative to the 25th percentile (24 °C). The cumulative relative risk for the weekly total rainfall over 12 weeks peaked at 82 mm (relative risk = 1.76, 95% confidence interval: 0.91–3.40) relative to no rain. However, the risk decreased significantly when heavy rain exceeded 200 mm. We found no evidence that altitude modified these associations.ConclusionsWe found a lagged nonlinear relationship between meteorological factors and dengue incidence in Lao PDR. These findings can be used to develop climate-based early warning systems and provide insights for improving vector control in the country.

Distributed lag effects and vulnerable groups of PM and active pulmonary TB in Qingdao, China.

There has been a gap regarding current knowledge of the effect of PM on pulmonary TB, such as the exposure-time-response between them. This study aimed to explore the distributed lag effects of particulate matter (PM) on active pulmonary tuberculosis (TB) and identify the vulnerable groups. A generalized additive mixed model combined with a distributed lag non-linear model was applied to quantify the association between PM and active pulmonary TB with adjustment for potential confounders. Relative risk (RR) and cumulative RR with 95% confidence interval (CI) were calculated to quantify the exposure-time-response. A total of 16,486 cases of active pulmonary TB were notified. Results suggested that a unit 10µg/m3 increase of daily PM2.5 concentration was positively associated with active pulmonary TB morbidity at 36-115 lag day and RR reached maximum at 66 lag day (1.0076; 95%CI, 1.0031-1.0122), and the cumulative RR was 2.1940 (95%CI, 1.2292-3.9161). For PM10, this association was significantly positive at 73-117 lag day, and RR reached maximum at 100 lag day (1.0036; 95%CI, 1.0003-1.0067), and the cumulative RR was not significant. This study provides evidence that PM significantly associate with active pulmonary TB. Vulnerability to PM2.5 was identified in male, female, 0-18 ages, 19-64 ages, workers, and students. Our findings have significant implications for developing local strategies to prevent and reduce health impact in PM polluted areas.