Recommendation on unbiased estimation of population attributable fraction calculated in"prevalence and risk factors of active pulmonary tuberculosis among elderly people in China:a population based cross-sectional study"

Population attributable fraction(PAF)refers to the proportion of all cases with a particular outcome in a population that could be prevented by eliminating a specific exposure.The authors of a recent paper evaluated the prevalence and estimated the PAFs for risk factors of TB among elderly people in China[Inf Dis Poverty.2019;8:7].Confounding is inevitable in observational studies and Levin’s formula is of limited use in practice for unbiasedly estimating PAF.In a complex survey design,an unbiased estimation of the PAF can be calculated using a sample-weighted version of the Miettinen formula or a sample weighed parametric g-formula.With respect to causal interpretation of PAF in public health setting,computation of PAF is logical and practical when the exposure is amenable to intervention.

Attributable Causes of Breast Cancer and Ovarian Cancer in China:Reproductive Factors,Oral Contraceptives and Hormone Replacement Therapy

Objective： To provide an evidence-based, consistent assessment of the burden of breast cancer attributable to reproductive factors （RFs, including nulliparity, mean number of children, age at first birth and breastfeeding）, use of oral contraceptives （OCs, restricted to the age group of 15-49 years）, and hormone replacement therapy （HRT）, as well as of the burden of ovarian cancer attributable to the mean number of children in China in 2005. Methods： We derived the prevalence of these risk factors and the relative risk of breast and ovarian cancer from national surveys or large-scale studies conducted in China. In the case of RFs, we compared the exposure distributions in 2001 and counterfactual exposure. Results： Exposure of RFs in 2002 was found to account for 6.74% of breast cancer, corresponding to 9,617 cases and 2,769 deaths, and for 2.78% of ovarian cancer （712 cases, 294 deaths）. The decrease in mean number of children alone was responsible for 1.47% of breast cancer and 2.78% of ovarian cancer. The prevalence of OC use was 1.74% and the population attributable fraction （PAF） of breast cancer was 0.71%, corresponding to 310 cases and 90 deaths. The PAF of breast cancer due to HRT was 0.31%, resulting in 297 cases and 85 deaths. Conclusion： RFs changes in China contributed to a sizable fraction of breast and ovarian cancer incidence and mortality, whereas HRT and OCs accounted for relatively low incidence of breast cancer in China.

Attributable deaths of liver cancer in China

Objective:There is little information about contributions of the well-known risk factors to the liver cancer burden.We conducted a comparative study to estimate the liver cancer burden attributable to major risk factors.Methods:Liver cancer deaths for adults were estimated from 978 county-level surveillance points in China in2014.Risk factors were identified from the International Agency for Research on Cancer and the World Cancer Research Fund International.Population attributable fraction(PAF)by age,sex,and province was calculated using multiple formulas.Results:In total,72.4%of liver cancer deaths could be attributable to the studied risk factors.Hepatitis B virus(HBV)was responsible for the largest fraction of liver cancer burden in both genders(PAF=55.6%in males,PAF=46.5%in females).PAFs for liver cancer burden attributable to smoking(15.7%vs.4.8%),and alcohol drinking(10.3%vs.1.6%)were significantly higher in males than in females.The burden of HBV-attributable deaths was the highest in Qinghai province.Conclusions:HBV still contributes to the majority of liver cancer burden than any other risk factors.Targeted preventive measures should be implemented based on the degree of contributions of risk factors to liver cancer deaths.

Attributable Causes of Cancer in China:Fruit and Vegetable

Objective：To provide an evidence-based and consistent assessment of the burden of cancer attributable to inadequate fruit and vegetable intake in China in 2005.Methods：The proportions of cancers attributable to low consumption of vegetable and fruit were calculated separately to estimate the burden of related cancers for the year 2005 in China.Data on the prevalence of exposure were derived from a Chinese nutrition and health survey.Data on relative risks were mainly derived from meta-analysis.Attributable fractions were calculated based on the counterfactual scenario which was a shift in the exposure distribution.Results：The total cancer burden attributable to inadequate consumption of fruit was up to 233,000 deaths （13.0% of all cancers） and 300,000 cases （11.6% of all cancers） in 2005.Increasing consumption of vegetable to the highest quintile could avoid total cancer deaths and cases by 3.6% （64,000 persons） and 3.4% （88,000 persons）.The contributions to cancer burden were higher in rural areas than in urban areas.They have greater influence on men than on women.The largest proportions of cancer burden attributable to low fruit and vegetable intake were for oral and pharyngeal cancers.Conclusion：This study showed that inadequate intake of fruit and vegetable makes a significant contribution to the cancer burden.Increasing consumption of fruit and vegetable could prevent many cancer deaths and save many lives.Promoting the consumption of fruit and vegetable is an important component in diet-based strategies for preventing cancer.

Total and cause-specific mortality attributable to cold spells in China:A multicity and multicounty study

Climate change has resulted in an increase in the frequency and intensity of extreme cold weather events,but few multicity or multicounty researches have explored the association between cold spells and mortality risk and burden.We collected daily data on climate,sociodemo-graphic factors and mortality in 18 cities/counties across 11 geographical regions for the period of November to March 2014-2018.A distributed lag nonlinear model was used to examine the association between cold spells and mortality after adjustment for confounding factors.Twelve definitions of cold spells were used.Multi-meta regression analysis was applied to pool the impacts over different regions.Cold spells were significantly associated with all-cause mortality at lag 0-21(CRR:1.38,95%CI:1.21,1.57).In addition to respiratory diseases and cir-culatory system diseases,digestive,endocrine and nervous system diseases and injury were also affected by cold spells.The magnitude of the impacts of cold spells on mortality varied among the diseases investigated,with the highest risk estimate found for influenza and pneumonia(CRR:2.00,95%CI:1.45,2.76)and the lowest estimate found for injury(CRR:1.26,95%CI:1.09,1.46).The fraction of all-cause mortality attributable to cold spells was 2.31%(95%CI:0.90%,3.46%).Among the regional differences,the attributable burden of all-cause mortality was higher in rural areas and subtropical monsoon climate zone,with attributable fractions of 2.85%(95%CI:1.23%,4.11%)and 3.36%(95%CI:0.55%,5.35%),respectively.Cold spells increased mortality from a range of diseases.Women,older adults and residents of rural areas and subtropical monsoon climate zone were more vulnerable to cold spells impacts.The findings may help to formulate preventive strategies and early warning response plans to reduce mortality burden of extreme cold events.

Association of heat exposure and emergency ambulance calls: A multi-city study

Evidence of the impact of ambient temperatures on emergency ambulance calls (EACs) in developing countries contributes to the improvement and complete understanding of the acute health effects of temperatures. This study aimed to examine the impacts and burden of heat on EACs in China, quantify the contributions of regional modifiers, and identify the vulnerable populations. A semi-parametric generalized additive model with a Poisson distribution was used to analyze the city-specific impacts of the daily maximum temperature (Tmax) on EACs in June–August in 2014–2017. Stratified analyses by sex and age were performed to identify the vulnerable sub-populations. Meta-analysis was undertaken to illustrate the pooled associations. Further subgroup analysis, stratified by climate, latitude, and per capita disposable income (PCDI), and meta-regression analysis were conducted to explore the regional heterogeneity and quantify the contributions of possible modifiers. The city- and region-specific attributable fractions of EACs attributable to heat were calculated. Strong associations were observed between the daily Tmax and total EACs in all cities. A total of 11.7% (95% confidence interval (CI): 11.2%–12.3%) of EACs were attributed to high temperatures in ten Chinese cities, and the central region with a low level of PCDI had the highest attributable fraction of 17.8% (95% CI: 17.2%–18.4%). People living in the central region with lower PCDI, and those aged 18–44 and 0–6 years were more vulnerable to heat than the others. The combined effects of PCDI, temperature, and latitude contributed 88.6% of the regional heterogeneity. The results complemented the understanding of the burden of EACs attributable to heat in developing countries and the quantitative contribution of regional modifiers.

Contribution of high risk groups’unmet needs may be underestimated in epidemic models without risk turnover:A mechanistic modelling analysis

Background:Epidemic models of sexually transmitted infections(STIs)are often used to characterize the contribution of risk groups to overall transmission by projecting the transmission population attributable fraction(tPAF)of unmet prevention and treatment needs within risk groups.However,evidence suggests that STI risk is dynamic over an individual’s sexual life course,which manifests as turnover between risk groups.We sought to examine the mechanisms by which turnover influences modelled projections of the tPAF of high risk groups.Methods:We developed a unifying,data-guided framework to simulate risk group turnover in deterministic,compartmental transmission models.We applied the framework to an illustrative model of an STI and examined the mechanisms by which risk group turnover influenced equilibrium prevalence across risk groups.We then fit a model with and without turnover to the same risk-stratified STI prevalence targets and compared the inferred level of risk heterogeneity and tPAF of the highest risk group projected by the two models.Results:The influence of turnover on group-specific prevalence was mediated by three main phenomena:movement of previously high risk individuals with the infection into lower risk groups;changes to herd effect in the highest risk group;and changes in the number of partnerships where transmission can occur.Faster turnover led to a smaller ratio of STI prevalence between the highest and lowest risk groups.Compared to the fitted model without turnover,the fitted model with turnover inferred greater risk heterogeneity and consistently projected a larger tPAF of the highest risk group over time.Implications:If turnover is not captured in epidemic models,the projected contribution of high risk groups,and thus,the potential impact of prioritizing interventions to address their needs,could be underestimated.To aid the next generation of tPAF models,data collection efforts to parameterize risk group turnover should be prioritized.

An extreme rainfall event in summer 2018 of Hami city in eastern Xinjiang, China

Extreme rainfall events are rare in inland arid regions, but have exhibited an increasing trend in recent years, causing many casualties and substantial socioeconomic losses. A series of heavy rains that began on July 31st, 2018, battered the Hami prefecture of eastern Xinjiang, China for four days. These rains sparked devastating floods, caused 20 deaths, eight missing, and the evacuation of about 5500 people. This study examines the extreme rainfall event in a historical context and explores the anthropogenic causes based on analysis of multiple datasets (i.e., the observed daily data, the global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), the NCEP/NCAR Reanalysis 1, and the satellite cloud data) and several statistical techniques. Results show that this extraordinarily heavy rainfall was due mainly to the abnormal weather system (e.g., the abnormal subtropical high) that transported abundant water vapor from the Indian Ocean and the East China Sea crossed the high mountains and formed extreme rainfall in Hami prefecture, causing the reservoir to break and form a flood event with treat loss, which is a typical example of a comprehensive analysis of the extreme rainfall event in summer in Northwest China. Also, the fraction of attributable risk (FAR) value was 1.00 when the 2018 July–August RX1day (11.52 mm) was marked as the threshold, supporting the claim of a significant anthropogenic influence on the risk of this extreme rainfall. The results offer insights into the variability of precipitation extremes in arid areas contributing to better manage water-related disasters.