The effects of temperature on human mortality in a Chinese city: burden of disease calculation, attributable risk exploration, and vulnerability identification

Effects of sunshine duration on daily outpatient visits for depression in Suzhou, Anhui Province, China

Previous epidemiological studies have reported seasonal variation patterns of depression symptoms, which may be influenced by bad weather conditions, such as a lack of sunlight. However, evidence on the acute effects of sunshine duration on outpatient visits for depression is limited, especially in developing countries, and the results are inconsistent. We collected daily outpatient visits for depression from the local mental health centre in Suzhou, Anhui Province, China, during 2017-2019. We defined the 5th and 95th sunshine percentiles as short and long sunshine durations, respectively. A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantitatively assess the effects of short and long sunshine durations on outpatient visits for depression. Stratified analyses were further performed by gender, age and number of visits to identify vulnerable populations. A total of 26,343 depression cases were collected during the study period. An approximate U-shaped exposure-response association was observed between sunshine duration and depression outpatient visits. The cumulative estimated relative risks (RRs) for short and long sunshine durations at lag 0-21 days were 1.53 [95% confidence intervals (CI): 1.14, 2.06] and 1.13 (95% CI: 0.88, 1.44), respectively. Moreover, a short sunshine duration was associated with a greater disease burden than a long sunshine duration, with attributable fractions (AFs) of 16.64% (95% CI: 7.8%, 23.89%) and 2.24% (95% CI: -2.65%, 5.74%), respectively. Subgroup analysis showed that males, people aged less than 45 years and first-visit cases may be more susceptible to a lack of sunlight. For a long sunshine duration, no statistically significant associations were found in any population groups. Our study found that a short sunshine duration was associated with an increased risk of depression. The government, medical institutions, family members and patients themselves should fully recognize the important role of sunlight and take active measures to prevent depression.

The Effectiveness of Intervening on Social Isolation to Reduce Mortality during Heat Waves in Aged Population: A Retrospective Ecological Study

BACKGROUND

Heat waves are correlated with increased mortality in the aged population. Social isolation is known as a vulnerability factor. This study aims at evaluating the correlation between an intervention to reduce social isolation and the increase in mortality in the population over 80 during heat waves.

METHODS

This study adopted a retrospective ecologic design. We compared the excess mortality rate (EMR) in the over-80 population during heat waves in urban areas of Rome (Italy) where a program to reduce social isolation was implemented, to others where it was not implemented. We measured the mortality of the summer periods from 2015 to 2019 compared with 2014 (a year without heat waves). Winter mortality, cadastral income, and the proportion of people over 90 were included in the multivariate Poisson regression.

RESULTS

The EMR in the intervention and controls was 2.70% and 3.81%, respectively. The rate ratio was 0.70 (c.i. 0.54-0.92, p-value 0.01). The incidence rate ratio (IRR) of the interventions, with respect to the controls, was 0.76 (c.i. 0.59-0.98). After adjusting for other variables, the IRR was 0.44 (c.i. 0.32-0.60).

CONCLUSIONS

Reducing social isolation could limit the impact of heat waves on the mortality of the elderly population.

Weather-related subjective well-being in patients with coronary artery disease

One of the particularly vulnerable groups for adverse weather conditions is people with heart disease. Most of the studies analyzed the association between certain weather conditions and increased mortality, morbidity, hospital admissions, calls, or visits to the emergency department and used as statistical data. This study evaluated associations between daily weather conditions and daily weather-related well-being in patients with coronary artery disease (CAD). From June 2008 to October 2012, a total of 865 consecutive patients with CAD (mean age 60 years; 30% of women) were recruited from the cardiac rehabilitation program at the Hospital Palanga Clinic, Lithuania. To evaluate the well-being, all patients filled in Palanga self-assessment diary for weather sensitivity every day from 8 to 21 days (average 15 ± 3 days) about their well-being (psychological, cardiac, and physical symptoms) on the last day. The weather data was recorded in the database eight times every day with a 3-hour interval using the weather station "Vantage Pro2 Plus" which was located in the same Clinic. The daily averages of the eight time records for weather parameters were calculated and were linked to the same-day diary data. We found that the well-being of patients with CAD was associated with weather parameters; specifically, general well-being was better within the temperature range 9-15 °C and worse on both sides of this range. Worsened general well-being was also associated with higher relative humidity and lower atmospheric pressure. Weather parameters can explain from 3 to 8% of the variance of well-being in patients with CAD.

Ambient Temperature and Years of Life Lost: A National Study in China

Although numerous studies have investigated premature deaths attributable to temperature, effects of temperature on years of life lost (YLL) remain unclear. We estimated the relationship between temperatures and YLL, and quantified the YLL per death caused by temperature in China. We collected daily meteorological and mortality data, and calculated the daily YLL values for 364 locations (2013–2017 in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces, and 2006–2011 in other locations) in China. A time-series design with a distributed lag nonlinear model was first employed to estimate the location-specific associations between temperature and YLL rates (YLL/100,000 population), and a multivariate meta-analysis model was used to pool location-specific associations. Then, YLL per death caused by temperatures was calculated. The temperature and YLL rates consistently showed U-shaped associations. A mean of 1.02 (95% confidence interval: 0.67, 1.37) YLL per death was attributable to temperature. Cold temperature caused 0.98 YLL per death with most from moderate cold (0.84). The mean YLL per death was higher in those with cardiovascular diseases (1.14), males (1.15), younger age categories (1.31 in people aged 65–74 years), and in central China (1.34) than in those with respiratory diseases (0.47), females (0.87), older people (0.85 in people ≥75 years old), and northern China (0.64) or southern China (1.19). The mortality burden was modified by annual temperature and temperature variability, relative humidity, latitude, longitude, altitude, education attainment, and central heating use. Temperatures caused substantial YLL per death in China, which was modified by demographic and regional characteristics.

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Years of life lost (YLL) is used to estimate the effects of temperature

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Both low and high temperatures can increase the YLLs

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Average 1.02 YLL per death is attributed to temperature exposure

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Temperature causes larger YLLs per death in males, younger people, and central China