Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Impact of Noise Exposure on Risk of Developing Stress-Related Metabolic Effects: A Systematic Review and Meta-Analysis

Background

Exposure to noise can increase biological stress reactions, which may increase adverse health effects, including metabolic disorders; however, the certainty in the association between exposure to noise and metabolic outcomes has not been widely explored. The objective of this review is to evaluate the evidence between noise exposures and metabolic effects.

Materials and Methods

A systematic review of English and comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases between January 1, 1980 and December 29, 2021 was performed. Risk of Bias of Nonrandomized Studies of Exposures was used to assess risk of bias of individual studies and certainty of the body of evidence for each outcome was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

Results

Fifty-six primary studies reporting on cortisol, cholesterol levels, waist circumference, glucose levels, and adrenaline and/or noradrenaline were identified. Although meta-analyses suggested that there may be an increase in waist circumference and adrenaline with increased noise exposure, the certainty in the evidence is very low. Overall, the certainty in the evidence of an effect of increased noise on all the outcomes were low to very low due to concerns with risk of bias, inconsistency across exposure sources, populations, and studies, and imprecision in the estimates of effects.

Conclusions

The certainty of the evidence of increased noise on metabolic effects was low to very low, which likely reflects the inability to compare across the totality of the evidence for each outcome. The findings from this review may be used to inform policies involving noise reduction and mitigation strategies, and to direct further research in areas that currently have limited evidence available.

Redox Switches in Noise-Induced Cardiovascular and Neuronal Dysregulation

Environmental exposures represent a significant health hazard, which cumulatively may be responsible for up to 2/3 of all chronic non-communicable disease and associated mortality (Global Burden of Disease Study and The Lancet Commission on Pollution and Health), which has given rise to a new concept of the exposome: the sum of environmental factors in every individual’s experience. Noise is part of the exposome and is increasingly being investigated as a health risk factor impacting neurological, cardiometabolic, endocrine, and immune health. Beyond the well-characterized effects of high-intensity noise on cochlear damage, noise is relatively well-studied in the cardiovascular field, where evidence is emerging from both human and translational experiments that noise from traffic-related sources could represent a risk factor for hypertension, ischemic heart disease, diabetes, and atherosclerosis. In the present review, we comprehensively discuss the current state of knowledge in the field of noise research. We give a brief survey of the literature documenting experiments in noise exposure in both humans and animals with a focus on cardiovascular disease. We also discuss the mechanisms that have been uncovered in recent years that describe how exposure to noise affects physiological homeostasis, leading to aberrant redox signaling resulting in metabolic and immune consequences, both of which have considerable impact on cardiovascular health. Additionally, we discuss the molecular pathways of redox involvement in the stress responses to noise and how they manifest in disruptions of the circadian rhythm, inflammatory signaling, gut microbiome composition, epigenetic landscape and vessel function.

Effect of Unmeasured Time Hours on Occupational Noise Exposure Assessment in the Shipbuilding Process in Korea

Occupational noise is known to be one of the most hazardous risk factors, frequently exceeding the exposure limit thus causing hearing loss and other health outcomes among many field workers in various industries and workplaces. This study aims to characterize the levels of occupational noise exposure during the daily working hours and break periods (sampling preparation and lunch break), identify work-related characteristics affecting the noise exposure levels when including or excluding the break periods and finally determine the most effective approach for occupational noise exposure assessment by using the Korean and U.S. OSHA’s guidelines. A total of 1575 workers employed by a large shipbuilding company participated in this study, and the historical exposure datasets of noise dosimeters, collected from 2016 to 2018, were classified by characteristics. A threshold level (TL) for the noise dosimeter was set as a value of 80 dBA during the break periods, including the preparation time for sampling instruments and one hour for the lunch break. The shipbuilding workers were exposed to high levels of occupational noise during the break periods, especially for those working in heating, grinding, and power processes in the painting-related departments. Out of 1575 samples, most cases were related to the preparation time (N = 1432, 90.9%) and lunch break (N = 1359, 86.9%). During the break time, the levels of noise exposure were measured depending on task-specific characteristics. When including the break time, the noise levels increased by approximately 1 dBA during the break, combining 0.8 dBA in the lunch hours and 0.2 dBA for the preparation of the sampling instrument. When excluding the break time, the levels of noise exposure collected using a Korean Occupational Safety and Health Administration (KOSHA) guide tended to be underestimated compared to those using the U.S. OSHA method. When including the break times, the proportion of noise exposure levels exceeding the compliance exposure limit declined from 37.9% to 34.5%, indicating that the break times might affect the decrease in the noise exposure levels. Taken together, shipbuilding workers could possibly be exposed to much greater amounts of noise exposure during break times in the shipbuilding processes, and the noise exposure levels in the department of painting were high. Therefore, it is recommended that industrial hygienists collect exposure monitoring data of occupational noise one hour after their job tasks begin and then consecutively monitor the noise exposure levels for at least 6 h including the break periods for each day.

Association of noise exposure with risk of metabolic syndrome: Evidence from 44,698 individuals

AIMS

Previous studies have explored the association between noise exposure and risk of metabolic syndrome (MetS); however, the results remain inconclusive.

METHODS

PubMed and Web of Science databases were searched through December 2020, multivariate-adjusted relative risks (RRs) were pooled by using random-effects models. Subgroup analysis was also conducted stratifying by gender, study location, study design, source of noise, study quality, adjusting for smoking, drinking, body mass index, physical activity and shift work.

RESULTS

Five studies involving 44,698 participants and 5187 MetS cases were included. A summarized adjusted RR for the relationship between noise exposure and risk of MetS was 1.27 (95% CI, 1.02-1.60), and 1.11 (1.02-1.21) for blood pressure and 1.11 (1.06-1.17) for blood glucose. Subgroup analysis revealed that the pooled risk of MetS was statistically significant in all cohort studies (RR = 1.34, 95 %CI, 1.06-1.68), ambient/traffic noise (RR = 1.24, 95 %CI, 1.13-1.35) and occupational noise by removing one low quality study (RR = 2.21, 95 %CI, 1.41-3.44).

CONCLUSIONS

Noise exposure is associated with an increased risk of MetS, and occupational noise exposure may result in a greater risk. Additional more prospective large-scale studies conducted in more countries or populations are needed to confirm the results, establish causality and elucidate the underlying mechanisms.

A systematic review and meta-analysis of the association between shift work and metabolic syndrome: The roles of sleep, gender, and type of shift work

This study was conducted to investigate the association between shift work and metabolic syndrome (MetS) and quantify the roles of sleep, gender, and type of shift work. We searched online databases, including PubMed, Scopus, and Web of Science on November 17, 2019. Of the 821 articles identified, 38 observational studies (27 cross-sectional, 10 cohorts, and one nested case-control), conducted on 128,416 participants, met our eligibility criteria. The pooled Odds ratio (OR) and 95% Confidence interval (CI) of MetS in shift-versus day-workers were estimated as 1.14 (1.07, 1.21) and 1.11 (1.06, 1.17) for the unadjusted and adjusted models. This association remained significant only for the studies with a cross-sectional design. There was a significantly higher odds of MetS in the studies conducted only on females (1.13 [1.06, 1.20]) or males (1.12 [1.02, 1.21]). The pooled adjusted OR (95% CI) for the studies without and with sleep adjustment was calculated as 1.14 (1.08, 1.21) and 1.29 (1.06, 1.52). We observed that rotating shift workers had stronger odds of MetS than the other shift workers. In conclusion, our findings revealed the significant odds of an association between shift work and MetS and different effects for sleep, gender, and type of shift work.

The association between road traffic noise and myocardial infarction: A systematic review and meta-analysis

This systematic review and meta-analysis study aimed to investigate the association between exposure to road traffic noise (RTN) and myocardial infarction (MI). Of 681 studies found by searching in databases, including Scopus, Web of Science, Embase, and PubMed on November 29, 2019, the number of 13 studies, including seven cohort, five case-control, and one cross-sectional studies with 1,626,910 participants and 45,713 cases of MI was included. The pooled relative risk (RR) and 95% confidence interval (CI) of MI were calculated using a random-effect model across studies. Heterogeneity measures by reporting the I-square index. Subgroup analysis according to the designs and sensitivity analysis based on the Jackknife approach was performed. We observed in the eight studies the association was investigated in different noise exposure groups and in the 10 studies (including two conference papers) the risk of MI was provided per specific unit increment of RTN. We ran two independent types of meta-analyses involving a categorical analysis (comparing the highest and the lowest category of noise exposure groups) and an exposure-response analysis (the risk of MI per 10-dB increment of RTN). The pooled RR (95% CI) of MI for the categorical and exposure-response meta-analyses was calculated 1.03 (0.93, 1.13) and 1.02 (1.00, 1.05), respectively. For both types of meta-analyses, subgroup analysis indicates a significant association in the studies with case-control and cross-sectional designs but not cohort studies. For the exposure-response meta-analysis, a significantly greater risk of MI was observed after excluding the two conference papers (RR = 1.03 and 95% CI = 1.00, 1.05) and by further excluding the studies provided originally the risk of MI only for the categorical analysis (RR = 1.02 and 95% CI = 1.01, 1.03). We did not show a significant publication bias across studies. In conclusion, our study suggests a significant odds of association between exposure to RTN and the risk of MI.