Exposure to outdoor artificial light at night increases risk and burden of metabolic disease in Ningxia, China

Nearly a quarter of the world's land has already been polluted by artificial light. And numerous human and animal studies have corroborated that light at night can disrupt metabolism. Therefore, we aimed to estimate the association between outdoor artificial light at night (ALAN) and the presence of metabolic disease. Daily hospital admission cases from Ningxia, China, between 2014 and 2020 were included. Cumulative associations between outdoor ALAN and metabolic disease were estimated using logistic regression and distributed lagged non-linear models (DLNM) with lags of 0-30 days and stratified analysis by age groups and gender. The results suggest that 26.80% of metabolic disease cases in Ningxia can be attributed to outdoor ALAN and that men, especially in men aged 46-59 years, are more susceptible to lighting. Policymakers need to develop measures and facilities in corresponding areas, such as universal access to indoor blackout curtains. In particular, men should be urged to minimize going outside at night and to develop protective measures specifically for men.

Association between ambient temperature and age-specific mortality from the elderly: Epidemiological evidence from the Chinese prefecture with most serious aging

Older people are main susceptible group affected by non-optimal temperature. The aim of the study was to determine how mortality of older people with different ages are affected by temperatures. For this study, we collected data of all-cause death of 256,037 people aged between 65 and 104 years of age from a prefecture located in the north subtropical area with most serious aging rate in 2000, 2010 and 2020 in China. A distributed lag nonlinear model under different age groups was used to estimate non-optimal temperature associations to mortality. The results revealed: (1) With increasing age, older people were more likely to die during moderate low temperature, the proportion of attributable fraction of moderate low temperature in all temperature gradually increased with age. (2) Moderate low temperature could be divided into two parts, the lower part caused most death at age 65-79 and the higher part was not so dangerous, while for age 80+, preventive actions should be taken for both parts. (3) A leveling-off and deceleration phenomenon was observed at age 95-99 for low temperature, but not 100-104, it may be virtually a consequence of "harvesting effect" in that susceptible and common people have died before age 95, it was coincidence with mortality deceleration at extreme old ages found by demographic scholars over the past 200 years. (4) Heat wave had much higher relative risk than cold spell compared with moderate high and low temperature because of steeper slope of relative risk at the period of moderate-extreme conversion of high temperature, the older people should pay more attention to weather with moderate-extreme conversion of high temperature. Furthermore, our findings could help improve the understanding of non-optimal temperature on health of older people and support the development of response strategies for different seasons at different ages.

Attributable fractions for substance use in relation to crime

AIMS

Building upon an existing methodology and conceptual framework for estimating the association between the use of substances and crime, we calculated attributable fractions that estimate the proportion of crimes explained by alcohol and six other categories of psychoactive substances.

DESIGN

Cross-sectional surveys.

SETTING

Canadian federal correctional institutions.

PARTICIPANTS

Canadian men (n = 27 803) and women (n = 1335) offenders who began serving a custodial sentence in a Canadian federal correctional institution between 2006 and 2016.

MEASUREMENTS

Offenders completed the computerized assessment of substance abuse, a self-report tool designed to assess (1) whether the offence for which they were convicted would have occurred had they not been intoxicated from alcohol or another substance, (2) whether they committed the offence to support their alcohol or other substance use and (3) whether they were dependent on alcohol (alcohol dependence scale) or another substance (drug abuse screening test). Offences were grouped into four mutually exclusive categories: violent crimes, non-violent crimes, impaired driving and substance-defined crimes. This study focused on violent and non-violent crime categories. Substances assessed were: alcohol, cannabis, opioids, other central nervous system (CNS) depressants, cocaine, other CNS stimulants and other substances.

FINDINGS

According to offender self-report, 42% of all violent and non-violent crime would probably not have occurred if the perpetrator had not been under the influence of, or seeking, alcohol or other substances. Between 2006 and 2016, 20% of violent crimes and 7% of non-violent crimes in Canada were considered attributable to alcohol. In contrast, all other psychoactive substance categories combined were associated with 26% of all violent crime and 25% of non-violent crime during the same time-frame.

CONCLUSIONS

Attributable fraction analyses show that more than 42% of Canadian crime resulting in a custodial sentence between 2006 and 2016 would probably not have occurred if the perpetrator had not been under the influence of or seeking alcohol or other drugs. Attributable fractions for alcohol and substance-related crime are a potentially useful resource for estimating the impact of alcohol and other substances on crime.

Years of life lost and mortality risk attributable to non-optimum temperature in Shenzhen: a time-series study

To assess YLL and mortality burden attributable to non-optimum ambient temperature, we collected mortality and environmental data from June 1, 2012 to December 30, 2017 in Shenzhen. We applied distributed lag nonlinear models with 21 days of lag to examine temperature-YLL and temperature-mortality associations, and calculated the attributable fractions of YLL and deaths for non-optimum temperature, including four subranges, mild cold, mild heat, extreme cold, and extreme heat. Cold and heat were distinguished by the optimum temperature, and each was separated into extreme and mild by cutoffs at 2.5th (12.2 °C) and 97.5th (30.4 °C) temperature percentile further. The optimum temperature was defined as the temperature that had minimum effect on YLL or mortality risk. The optimum temperature for non-accidental YLL was 24.5 °C, and for mortality it was 25.4 °C. Except for the population older than 65 years, the optimum temperature was generally lower in the YLL model than the mortality model. Of the total 61,576 non-accidental deaths and 1,350,835.7 YLL within the study period, 17.28% (95% empirical CI 9.42-25.14%) of YLL and 17.27% (12.70-21.34%) of mortality were attributable to non-optimum temperature. More YLL was caused by cold (10.14%, 3.94-16.36%) than by heat (7.14%, 0.47-13.88%). Mild cold (12.2-24.5 °C) was responsible for far more YLL (8.78%, 3.00-14.61%) than extreme cold (3.5-12.2 °C). As for cardiovascular deaths, only the fractions attributable to overall and cold temperature were significant, with mild cold contributing the largest fraction to YLL (16.31%, 6.85-25.82%) and mortality (16.08%, 9.77-21.22%). Most of the temperature-related YLL and mortality was attributable to mild but non-optimum weather, especially mild cold, while the YLL model implied a more prominent heat effect on premature death. Our findings can supply additional evidence from multiperspectives for health planners to define priorities and make targeted policies for mitigating the burden of adverse temperatures.

Economic burden of work injuries and diseases: a framework and application in five European Union countries

BACKGROUND

Estimates of the economic burden of work injuries and diseases can help policymakers prioritize occupational health and safety policies and interventions in order to best allocate scarce resources. Several attempts have been made to estimate these economic burdens at the national level, but most have not included a comprehensive list of cost components, and none have attempted to implement a standard approach across several countries. The aim of our study is to develop a framework for estimating the economic burden of work injuries and diseases and implement it for selected European Union countries.

METHODS

We develop an incidence cost framework using a bottom-up approach to estimate the societal burden of work injuries and diseases and implement it for five European Union countries. Three broad categories of costs are considered-direct healthcare, indirect productivity and intangible health-related quality of life costs. We begin with data on newly diagnosed work injuries and diseases from calendar year 2015. We consider lifetime costs for cases across all categories and incurred by all stakeholders. Sensitivity analysis is undertaken for key parameters.

RESULTS

Indirect costs are the largest part of the economic burden, then direct costs and intangible costs. As a percentage of GDP, the highest overall costs are for Poland (10.4%), then Italy (6.7%), The Netherlands (3.6%), Germany (3.3%) and Finland (2.7%). The Netherlands has the highest per case costs (€75,342), then Italy (€58,411), Germany (€44,919), Finland (€43,069) and Poland (€38,918). Costs per working-age population are highest for Italy (€4956), then The Netherlands (€2930), Poland (€2793), Germany (€2527) and Finland (€2331).

CONCLUSIONS

Our framework serves as a template for estimating the economic burden of work injuries and diseases across countries in the European Union and elsewhere. Results can assist policymakers with identifying health and safety priority areas based on the magnitude of components, particularly when stratified by key characteristics such as industry, injury/disease, age and sex. Case costing can serve as an input into the economic evaluation of prevention initiatives. Comparisons across countries provide insights into the relevant performance of health and safety systems.

Etiology of diarrhea by multiplex polymerase chain reaction among young children in the United Arab Emirates: a case-control study

Background

Little is known about the etiology of childhood diarrhea in the United Arab Emirates (UAE) especially after the introduction of rotavirus vaccines. This study aimed to identify gastrointestinal pathogens in children with diarrhea (cases) and the carriage rate of these pathogens in asymptomatic children (controls).

Methods

Stool samples were collected from 203 cases and 73 controls who presented to two major hospitals in Al Ain city, UAE. Samples were analyzed with Allplex™ Gastrointestinal Full Panel Assay for common entero-pathogens. The association between diarrhea and the isolated pathogens was calculated in a multivariate logistic regression model. The adjusted attributable fractions (aAFs) were calculated for all pathogens significantly associated with cases.

Results

At least one pathogen was identified in 87 samples (42.8%) from cases and 17 (23.3%) from controls (P < 0.001). Rotavirus, norovirus GII and adenovirus were significantly more prevalent in cases. Their aAFs with 95% ci are 0.95 (0.64, 1.00) for rotavirus, 0.86 (0.38, 0.97) for norovirus GII and 0.84 (0.29, 0.96) for adenovirus. None of the 13 bacteria tested for were more commonly found in the cases than in controls. Cryptosporidium spp. were more significantly detected in cases than in controls. Co-infections occurred in 27.9% of the children. Viruses and parasites were significantly more likely to occur together only in the cases.

Conclusions

Multiplex PCR revealed high positivity rates in both cases and controls which demand a cautious interpretation. Rotavirus remains the main childhood diarrhea pathogen in UAE. Effective strategies are needed to better control rotavirus and other causative pathogens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-020-05693-1.

Association between moderately cold temperature and mortality in China

Ambient air temperature is a key factor affecting human health. Adverse effects of extreme weather on mortality have been well explored and expounded in numerous epidemiological studies. The relationship between moderate temperature and mortality is, however, underexplored. This study quantitatively investigated the temperature-dependent mortality burden in China. Data on daily average temperature and mortality in 15 Chinese cities during 2010-2016 were collected for this study. The association between temperature and city-specific mortality was investigated with a quasi-Poisson regression combined with a distributed lag nonlinear model across lag 0-21 days. The results were then included in a multivariate meta-analysis to derive the pooled estimates of the effect of temperature on mortality at the multi-city level. Mortality fractions attributable to cold and heat (i.e., at temperatures below and above the minimum mortality temperature (MMT)) were calculated. Additionally, temperature ranges were further divided into 1 °C intervals of ambient temperature, and the attributable fractions were calculated for each range. The MMT varied from the 71th to 93th percentiles of temperature in the 15 Chinese cities, centering at the 78th percentile at the multi-city level. In total, 12.65% of non-accidental mortality was attributable to non-optimum temperature, of which cold and hot temperatures corresponded to attributable fractions of 11.38% and 1.27%, respectively. The results of temperature stratifications suggested that moderately cold temperatures provided the highest contribution to mortality caused by temperature. Specifically, the highest attributable fractions were at 7 °C, 7 °C, 8 °C, 8 °C, 4 °C, 4 °C, 5 °C, 7 °C, 7 °C, 4 °C, 5 °C, 5 °C, 6 °C, 11 °C, and 12 °C, for Harbin, Changchun, Shenyang, Urumqi, Beijing, Tianjin, Shijiazhuang, Xining, Lanzhou, Nanjing, Shanghai, Hefei, Chengdu, Kunming, and Guangzhou, respectively. Cold temperature was responsible for a higher proportion of deaths than heat. Moderate cold temperature contributed to most of the total health burden. Finally, the cumulative total counts of deaths caused by moderate cold were the largest. Although moderate cold conferred a slightly lower relative risk than extreme cold, it was more common than extreme cold. Taken together, our results show that the effects of moderate cold temperature on health should receive more attention. Furthermore, our findings could help improve the prediction of climate change effects on human health and support the development of response strategies for the changing climate.

Accounting for biases in survey-based estimates of population attributable fractions

BACKGROUND

This paper discusses best practices for estimating fractions of mortality attributable to health exposures in survey data that are biased by observed confounders and unobserved endogenous selection. Extant research has shown that estimates of population attributable fractions (PAF) from the formula using the proportion of deceased that is exposed (PAF_pd) can attend to confounders, whereas the formula using the proportion of the entire sample exposed (PAF_pe) is biased by confounders. Research has not explored how PAF_pd and PAF_pe equations perform when both confounding and selection bias are present.

METHODS

We review equations for calculating PAF based on either the proportion of deceased (pd) or the proportion of the entire sample (pe) that receives the exposure. We explore how estimates from each equation are affected by confounding bias and selection bias using hypothetical data and real-world survey data from the National Health Interview Survey-Linked Mortality Files, 1987-2011. We examine the association between cigarette smoking and all-cause mortality risk in the US adult population as an example.

RESULTS

We show that both PAF_pd and PAF_pe calculate the true PAF in the presence of confounding bias if one uses the "weighted-sum" approach. We further show that both the PAF_pd and PAF_pe calculate biased PAFs in the presence of collider bias, but that the bias is more severe in the PAF_pd formula.

CONCLUSION

We recommend that researchers use the PAF_pe formula with the weighted-sum approach when estimates of the exposure-outcome relationship are biased by endogenous selection.

State-level diabetes-attributable mortality and years of life lost in the United States

PURPOSE

To estimate state-level diabetes-attributable deaths and years of life lost (YLL) in the Unites States.

METHODS

We estimated diabetes-attributable all-cause and cardiovascular disease (CVD) deaths by age, sex, and state, using the attributable fraction approach. Data on diabetes prevalence were collected from Behavioral Risk Factor Surveillance System. Relative risks for people with and without diabetes were estimated using the National Health Interview Survey. State-sex-age-specific deaths were obtained from CDC WONDER. YLL were calculated by multiplying the number of people with diabetes by the difference in life expectancy between people with and without diabetes using the life table approach.

RESULTS

Nationally, estimated diabetes-attributable all-cause deaths and CVD deaths were 293,224 and 90,953, respectively. Diabetes resulted in a total of 109,707,000 YLL with an average 4.4 years of life lost per person with diabetes. Most state variation in total deaths was explained by state population size and diabetes prevalence. All-cause deaths ranged from 415 in Alaska to 28,538 in California, and CVD deaths ranged from 113 in Alaska to 8908 in California. Across all states, the average diabetes-attributable death rate per 100,000 was 125 for males and 105 for females for all-cause deaths and 40 for males and 31 for females for CVD deaths.

CONCLUSIONS

Mortality attributable to diabetes is greatly underestimated when looking only at diabetes listed as an underlying cause of death. These results can be used to track state differences in deaths due to diabetes and to monitor the success of public health activities.

Population attributable fractions for Type 2 diabetes: an examination of multiple risk factors including symptoms of depression and anxiety

BACKGROUND

Population attributable fractions (PAFs) are frequently used to quantify the proportion of Type 2 diabetes cases due to single risk factors, an approach which may result in an overestimation of their individual contributions. This study aimed to examine Type 2 diabetes incidence associated with multiple risk factor combinations, including the metabolic syndrome, behavioural factors, and specifically, depression and anxiety.

METHODS

Using data from the population-based HUNT cohort, we examined incident diabetes in 36,161 Norwegian adults from 1995 to 2008. PAFs were calculated using Miettinen's case-based formula, using relative risks estimated from multivariate regression models.

RESULTS

Overall, the studied risk factors accounted for 50.5% of new diabetes cases (78.2% in men and 47.0% in women). Individuals exposed to both behavioural and metabolic factors were at highest risk of diabetes onset (PAF = 22.9%). Baseline anxiety and depression contributed a further 13.6% of new cases to this combination. Men appeared to be particularly vulnerable to the interaction between metabolic, behavioural and psychological risk factors.

CONCLUSION

This study highlights the importance of risk factor clustering in diabetes onset, and is the first that we know of to quantify the excess fraction of incident diabetes associated with psychological risk factor interactions.