Assessment of evidence on reported non-genetic risk factors of congenital heart defects: the updated umbrella review.

BACKGROUND: Congenital heart defect (CHD) is the leading cause of birth defects globally, which results in a great disease burden. It is still imperative to detect the risk factors of CHD. This umbrella review aimed to comprehensively summarize the evidence and grade the evidence of the associations between non-genetic risk factors and CHD. METHODS: Databases including Medline, Embase, Web of Science, Cochrane Library, and four Chinese databases were searched from inception to 18 Jan 2022. The reference lists of systematic reviews (SR) and meta-analyses (MA) were screened, which aimed to explore the non-genetic risk factors of CHD. Subsequently, titles and abstracts of identified records and full texts of selected SR/MA were screened by two independent reviewers based on predefined eligibility criteria. A priori developed extraction form was used to abstract relative data following the PRISMA 2020 and MOOSE guidelines. The risk of bias was assessed with the AMSTAR2 instrument. Data were synthesized using fixed-effects and random-effects meta-analyses, respectively. Finally, the evidence on the association of non-genetic risk factors and CHD was graded using Ioannidis's five-class evidence grade. RESULTS: A total of 56 SRs, encompassing 369 MAs, were identified. The risk factors included relative factors on air pollution, reproductive-related factors, parental age and BMI, parental life habits, working and dwelling environment, maternal drug exposure, and maternal disease. Based on AMSTAR2 criteria, only 16% (9/56) of SRs were classified as "Moderate". One hundred and two traceable positive association MAs involving 949 component individual studies were included in further analysis and grading of evidence. Family genetic history, number of abortions, maternal obesity, especially moderate or severe obesity, decoration materials, harmful chemicals, noise during pregnancy, folic acid supplementation, SSRIs, SNRIs, any antidepressants in the first trimester, maternal DM (including both PGDM and GDM), and gestational hypertension were convincing and highly suggestive factors for CHD. After sensitivity analyses based on cohort studies, some grades of evidence changed. CONCLUSION: The present umbrella review will provide evidence-based information for women of childbearing age before or during pregnancy to prevent CHD. In addition, sensitivity analysis based on cohort studies showed the changed evidence levels. Therefore, future SR/MA should concern the sensitivity analysis based on prospective birth cohort studies and case-control studies.

The household economic burden of non-communicable diseases in 18 countries.

Background: Non-communicable diseases (NCDs) are the leading cause of death globally. In 2014, the United Nations committed to reducing premature mortality from NCDs, including by reducing the burden of healthcare costs. Since 2014, the Prospective Urban and Rural Epidemiology (PURE) Study has been collecting health expenditure data from households with NCDs in 18 countries. Methods: Using data from the PURE Study, we estimated risk of catastrophic health spending and impoverishment among households with at least one person with NCDs (cardiovascular disease, diabetes, kidney disease, cancer and respiratory diseases; n=17 435), with hypertension only (a leading risk factor for NCDs; n=11 831) or with neither (n=22 654) by country income group: high-income countries (Canada and Sweden), upper middle income countries (UMICs: Brazil, Chile, Malaysia, Poland, South Africa and Turkey), lower middle income countries (LMICs: the Philippines, Colombia, India, Iran and the Occupied Palestinian Territory) and low-income countries (LICs: Bangladesh, Pakistan, Zimbabwe and Tanzania) and China. Results: The prevalence of catastrophic spending and impoverishment is highest among households with NCDs in LMICs and China. After adjusting for covariates that might drive health expenditure, the absolute risk of catastrophic spending is higher in households with NCDs compared with no NCDs in LMICs (risk difference=1.71%; 95% CI 0.75 to 2.67), UMICs (0.82%; 95% CI 0.37 to 1.27) and China (7.52%; 95% CI 5.88 to 9.16). A similar pattern is observed in UMICs and China for impoverishment. A high proportion of those with NCDs in LICs, especially women (38.7% compared with 12.6% in men), reported not taking medication due to costs. Conclusions: Our findings show that financial protection from healthcare costs for people with NCDs is inadequate, particularly in LMICs and China. While the burden of NCD care may appear greatest in LMICs and China, the burden in LICs may be masked by care foregone due to costs. The high proportion of women reporting foregone care due to cost may in part explain gender inequality in treatment of NCDs.

Ethnic differences in spirometry measurements in China: Results from a large community-based epidemiological study.

BACKGROUND AND OBJECTIVE: No previous studies have examined differences in spirometry measurements among ethnic populations in China, and factors which may influence ethnic differences are unclear. Our study aimed to investigate whether forced expiratory volume in 1 s (FEV1 ) and forced vital capacity (FVC) differ among Han Chinese and other ethnic minorities in China. METHODS: We recruited 7137 individuals aged 35-70 years from four areas of China inhabited by ethnic minority groups between 2007 and 2009. We conducted spirometry tests for all available participants, and compared FEV1 and FVC among Uygur, Hui, Mongolian, Dai and Han Chinese ethnicities, using nonlinear multiplicative regression models. RESULTS: A total of 2005 healthy never-smokers were enrolled in the analysis. For all ethnicities, spirometry values increased with height and decreased with age; FEV1 and FVC were consistently higher in males than in females. Compared with Han Chinese, FEV1 was 4.42% (95% CI: 2.11-6.78%) higher in Mongolians, 4.08% (95% CI: 1.33-6.76%) lower in Uygurs, 4.39% (95% CI: 1.33-7.35%) lower in Hui people and 4.72% (95% CI: 1.80-7.55%) lower in Dai people, after adjusted for potential confounders including height, age, sex and place of residence. We observed similar differences for FVC. CONCLUSIONS: We detected significant differences in spirometry measurements among ethnic populations in China. Such differences cannot be fully explained by demographic, anthropometric or socioeconomic factors, but may also be attributed to genetic background as well as indoor and outdoor environmental exposures that need further investigation.

Cardiovascular Diseases and Risk-Factor Burden in Urban and Rural Communities in High-, Middle-, and Low-Income Regions of China: A Large Community-Based Epidemiological Study.

BACKGROUND: Most cardiovascular diseases occur in low- and middle-income regions of the world, but the socioeconomic distribution within China remains unclear. Our study aims to investigate whether the prevalence of cardiovascular diseases differs among high-, middle-, and low-income regions of China and to explore the reasons for the disparities. METHODS AND RESULTS: We enrolled 46 285 individuals from 115 urban and rural communities in 12 provinces across China between 2005 and 2009. We recorded their medical histories of cardiovascular diseases and calculated the INTERHEART Risk Score for the assessment of cardiovascular risk-factor burden, with higher scores indicating greater burden. The mean INTERHEART Risk Score was higher in high- and middle-income regions than in low-income regions (9.47, 9.48, and 8.58, respectively, P<0.0001). By contrast, the prevalence of total cardiovascular disease (stroke, ischemic heart disease, and other heart diseases that led to hospitalization) was lower in high- and middle-income regions than in low-income regions (7.46%, 7.42%, and 8.36%, respectively, Ptrend=0.0064). In high- and middle-income regions, urban communities have higher INTERHEART Risk Score and higher prevalent rate than rural communities. In low-income regions, however, the prevalence of total cardiovascular disease was similar between urban and rural areas despite the significantly higher INTERHEART Risk Score for urban settings. CONCLUSIONS: We detected an inverse trend between risk-factor burden and cardiovascular disease prevalence in urban and rural communities in high-, middle-, and low-income regions of China. Such asymmetry may be attributed to the interregional differences in residents' awareness, quality of healthcare, and availability and affordability of medical services.