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Mediterranean Diet and Invasive Breast Cancer Risk Among Women at High Cardiovascular Risk in the PREDIMED Trial: A Randomized Clinical Trial. JAMA Intern Med. 2015 Nov;175(11):1752-1760.

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Mediterranean Diet and Invasive Breast Cancer Risk Among Women at High Cardiovascular Risk in the PREDIMED Trial: A Randomized Clinical Trial. JAMA Intern Med. 2015 Nov;175(11):1752-1760.

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ENLACE DE ESTUDIO: https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2434738

Este estudio se trata de un estudio de tipo experimental, tipo ensayo de campo, que se aplica a un grupo de personas sanas para evaluar el efecto de una determinada intervención, llevado a cabo en varios centros médicos de España. En este caso la intervención es la dieta mediterránea y el uso de aceite de oliva extra virgen vs. consumo de nueces vs. alimentación estándar y el efecto a evaluar es el impacto en prevención primaria de cáncer de mama. El estudio inicial buscaba evaluar prevención primaria de riesgo cardiovascular pero este artículo reporta los hallazgos en cáncer de mama. El desenlace se considera como presente, si se encontraron nuevos casos de cáncer de mama.
La intervención se clasificó en 3 grupos; Dieta con alto uso de aceite extravirgen, consumo de nueces y grupo control.
Este es el tipo de estudio perfecto para éste tema porque
su objetivo es evaluar intervenciones que puedan prevenir la aparición de una enfermedad que es poco frecuente y que requiere investigación en una población grande. Es un estudio con alta inversión económica y logística.

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Ecological study of ambient air pollution exposure and mortality of cardiovascular diseases in elderly. Samaneh Dehghani et al. Sci Rep. 2022 Dec 9;12(1):21295. doi: 10.1038/s41598-022-24653-0.

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Ecological study of ambient air pollution exposure and mortality of cardiovascular diseases in elderly. Samaneh Dehghani et al. Sci Rep. 2022 Dec 9;12(1):21295. doi: 10.1038/s41598-022-24653-0.

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Los estudios ecológicos suelen ser el punto de partida para el estudio de nuevas investigaciones sobre temas muy importantes en salud pública y Nature como revista es una de las más famosas como publicaciones de nuevo conocimiento.
En el caso de exposición ambiental por polución del aire, cada vez se publican más artículos que muestran la importancia de ésta exposición.
Este artículo es de 2022 y encontró que la contaminación del aire está directa e indirectamente relacionada con mortalidad cardiovascular además que aumenta la prevalencia de factores de riesgo cardiovasculares en Iran.
La debilidad de éstos estudios, es que como la unidad de evaluación es una población y no el individuo, no se puede establecer la relación individual directamente entre exposición y efecto.
Si bien es una buena aproximación para otros estudios, debemos tener cuidado con la falacia ecológica y evitar realizar atribuciones a la exposición directamente, sin que se puedan controlar otras variables que afecten el desenlace.

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Introduction

Exposure to air pollution increments morbidity and mortality of cardiovascular disease (CVD)1, especially exposure to emissions from traffic and industrial sources2. Even lower concentrations of exposure to particulate matter (PM) caused by combustion, as a significant component of urban pollution, are involved in the pathogenesis of CVD3. Some researchers have shown a relationship between intense or persistent exposure to PM and the rate of cardiopulmonary occasions4. Increased ambient air pollution (AAP) can be considered a risk factor for heart failure5, myocardial infarction, cardiovascular stroke6, and death7,8. These effects can be due to intense daily variation in air pollutant levels just as lifelong exposure to them1. Long-term exposure to PM air pollution per 10 μg/m ³ is estimated to increase the overall mortality rate by 2-4%, with the highest mortality rate from CVD2.

Although the etiology underlying this long-term relationship is unknown9, Some pathways are considered as possible biological mechanisms for increased risk of CVD incidence due to air pollution exposure. Disorders of the autonomic nervous system of the heart, pulmonary and systemic oxidative stress and inflammatory responses that impair endothelial function, atherosclerosis, and thrombosis have been reported as direct effects of AAP10. Long-term air pollutants exposure at low levels participates in hypertension11, obesity12,13, and diabetes14, which are involved in the CVD epidemiology15. Hence, AAP indirectly affects CVD risk through changes in blood pressure, triglyceride, blood sugar, and vascular functions16.

Iran's aging population will be forecasted to be 10.5% in 2025 and 21.7% in 2050, following the oldest population in the region by 205017. Despite the medical advances in treatment and control of CVD, which have prompted a significant decrease in CVD rate, prevention is still considered a priority, especially to reduce clinical expenses18,19. Due to the vulnerability of the cardiovascular system to environmental factors reported in previous studies in other earas20,21, this ecological research was performed aimed to analyze 1- the relationship between AAP exposure and CVD mortality as the first cause of death in Iran, 2- the relationship between exposure to AAP and the prevalence of traditional risk factors for CVD, including diabetes, hypertension, obesity, and high LDL cholesterol in Iranian over 50 years of age in 1990-2019.

Materials and methods

Data collection

Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. Data on CVD mortality was collected separately for each year from 1990 to 2019 in Iran based on sex and age groups of 50-69 years and over 70 years22,23. In addition, the prevalence of traditional CVD risk factors collected by year and in the age and sex groups of 50-69 years and over 70 years, tobacco use, smoking, diabetes mellitus type 2 (DM2), high LDL cholesterol, high body mass index (BMI), and high systolic blood pressure (SBP). The definition of the elderly group with a reference for considering 50 years old as a cut point of age for the elderly group was considered.

The blood low-density lipoprotein (LDL) concentration is estimated in mmol/L, and the theoretical minimum risk exposure level value (TMREL) is used with a uniform distribution between 0.7 and 1.3 mmol/L. The values of brachial SBP are estimated in millimeters of mercury, and TMREL SBP 110 to 115 mm of mercury is used. DM is characterized collectively as a metabolic disease whose common component is a raised blood glucose level (hyperglycemia). Also, adults' high BMI (ages 20 and up) is characterized as a BMI of more than 20-25 kg body weight in the second power of height (meters)22. Air pollution exposure in this study is defined as ambient particulate air pollution (PM), ambient ozone pollution, and air pollution (the sum of PM and ozone pollution) based on the Global Burden of Disease (GBD) categorization in micrograms per cubic meter (µg/m ³). Satellite data has been used to measure air pollution22.

GBD dataset uses many different sources to populate the information in the GHDx. Most information about datasets and series comes from the data providers; also was used many of the resources are noted on the Data Sites We Love page, particularly are indebted to organizations such as IPUMS, ICPSR, and the World Bank. For older data, WorldCat is an invaluable resource. All of the data is collected from the following official websites: http://www.healthdata.org/.

Based on the GBD 2019 study, this site covers injuries and risk factors from 1990 to 2019, covering 204 countries and territories. In total, 369 causes of illness and injury were systematically analyzed. The methodology of the GBD studies and the principal changes incorporated into the GBD 2019 method has been explained in detail elsewhere24.

Statistical analysis

Excel software was used for preliminary analysis, including graphs and maps. Then the information was prepared to enter the joinpoint software. Descriptive analysis for CVD mortality was performed using the regression model in the Joinpoint software (version 4.9.0.0). The joinpoint software is one of the statistical software available by the American Cancer Society to perform joinpoint regression. The latest version of the software was used to perform the regression analysis of attachment points. The regression of attached points actually forms segments by creating statistically significant points compared to the previous point, and for each segment or piece, an APC (annual percentage change) or annual percentage change will be created. In addition, the software provides average annual percentage change or AAPC (Average Annual percentage change). With these two values, the trend of changes from 1990 to 2019 was investigated. We reported the APC, AAPC, and related confidence intervals in the Iranian male and female populations over 50 years old separately. The Descriptive results of the PM data section, the mortality data related to ambient particulate matter pollution exposure, particulate matter pollution exposure, and air pollution exposure are reported separately in the method section of the jointpoint regression model as well as deathes due to the CVD. Spearman's correlation was utilized to investigate the relationships between ambient air pollution data and specific CVD mortality rates and the prevalence of high SBP, high BMI, DM2, high LDL cholesterol, and other risk factors in the R software (version 3.5.0).

Correlations of air pollution-related mortality or prevalences for each corresponding year are analyzed. All statistical analyses were two-sided, and a p-value less than 0.05 (p < 0.05) was considered significant. Correlation intensity was interpreted based on correlation values; r = 0.8-1 very strong correlation, r = 0.6-0.08 strong correlation, r = 0.4-0.6 moderate correlation, r = 0.2-0.4 low or weak correlation relationship25. The detail of the plan of the study was shown in the Fig. 1.

Results and discussion

One of the most controversial issues related to climate is urban development and its pollution. Researches on air pollutants and climatic elements suggest a link between the two factors and the mortality and incidence of disease. The extent to which the climate effect the severity of many diseases, including lung, heart, infectious and contagious diseases, is undeniable26. Cardiovascular failure is a major general health problem that influences over 23 million people worldwide, with a 1-year mortality rate of 30% and a rate of annual hospitalization of 2%. Recently, AAP has been considered a short-term trigger in developing heart failure27,28,29,30. The present study uses recorded data on mortality of the CVD and risk factors for this disease (DM2, high LDL cholesterol, high BMI, and high SBP) in age groups above 50 years and its relationship with recorded data from air pollution from 1990 to 2019.

Descriptive results of CVD mortality data

Deaths distribution of ischemic heart disease in 1990 and 2019 by provinces of Iran per 100,000 was shown in Fig. 2.

Distribution of deaths due to CVD per 100,000 by provinces of Iran in 1990 ( a) and 2019 ( b).

Descriptive results of CVD mortality data from 1990 to 2019 in people 50-69 years old and over 70 years by gender were shown in Figs. 3 and 4, respectively. These results indicate that the mortality resulting from CVD in males 50-69 years and over 70 years had a downward trend [AAPC = −2.6% (CI: −2.8 to −2.4), AAPC = −2.5% (CI: −2.6 to −2.4), respectively] and also had a descending direction in females ranges 50-69 years and above 70 years old [AAPC = −0.7% (CI: −0.8 to −0.6), AAPC = −0.6% (CI: −0.8 to −0.4), respectively] (see in Table 1). The latest GBD study estimates that in 2019, there were 8.76 million disability-adjusted life years (DALYs, 146,000 deaths among females, and 131,000 deaths among males due to cardiovascular and circulatory diseases31.

Descriptive results of PM data

Descriptive results of mortality data data on ambient particulate matter exposure, particulate matter pollution, ambient ozone exposure, and air pollution exposure from 1990 to 2019 in over 50 years males and females were shown in Figs. 5, 6, 7 and 8, respectively.

These results showed that mortality due to exposure to ambient particulate matter pollution in females over 50 years had an uptrend trend [AAPC = 0.85% (CI: 0.7 to 1.01), respectively] and also had an ascending direction in males over 50 years [AAPC = 0.37% (CI: 0.23 to 0.50), respectively] (see in Table 2).

Mortality due to exposure to particulate matter in females over 50 years had an ascending direction [AAPC = 0.07% (CI: −0.1 to 0.23), respectively] and had a downward trend in males over 50 years [AAPC = −0.23% (CI: −0.46 to 0.0), respectively] (see in Table 3).

Mortality due to exposure to ambient ozone in females an males over 50 years had an ascending trend [AAPC = 0.71% (CI: −0.25 to 1.68)] 50 years [AAPC = 1% (CI: 0.12 to 1.90)], respectively (see in Table 4).

Finally, the mortality resulting from exposure to air pollution in males over 50 years had a downward trend [AAPC = −0.18% (CI: −0.4 to 0.04), respectively] and had a uptrend in females over 50 years [AAPC = 0.13% (CI: 0.0 to −0.26), respectively] (see in Table 5).

Recently, air pollution has become a significant phenomenon, especially in developing countries, due to the increase of vehicles, congested traffic, inappropriate control of the release of pollutants from the resources, industrialization, and improper laws32,33. So, in this situation, air pollution has an increasing trend34. Particulate matter (PM), which was emitted due to biogenic and anthropogenic sources and produced by atmospheric reactions, is deliberated as the averse airborne pollutants35. Currently, West Asia is affected by dust storms in deserts, raising the number of dusty days and PM's daily average (PM ₁₀)36,37. PM ₁₀ can penetrate thoroughly into the airways and cause severe health effects on humans38,39.

Particulate air pollution and its harmful health impacts are not newborn dilemmas40. Recently, scientists have examined what characteristics of ambient aerosol caused the health impacts and whether chemical components of specific particulate have higher health effects than others41. There is a significant relation between dust events and daily hospitals because of respiratory illnesses in Asia42,43,44. Epidemiological inquiries have illustrated the detrimental impacts of PM air pollution on cardiorespiratory conditions45,46. Moreover, PM exposure has caused oxidative stress and systemic inflammation, as mentioned in some research47,48. Therefore there is an authoritative relationship between ambient exposure to air pollution and cardiopulmonary morbidity and mortality48,49.

Ambient air pollution exposure and CVD mortality

The relationship between CVD mortality and AAP levels is shown in Fig. 9. There was significant relationship and positive correlation between CVD mortality and ambient PM (p ≤ 0.001, r = 0.99), ambient ozone pollution (p ≤ 0.001, r = 0.94), and ambient air pollution (p ≤ 0.001, r = 0.99) in over 50 years adults in Iran.

Brook et al.'s research estimated that 69% of early deaths result in CVD, comprising ischemic heart disease and stroke, while lung disease accounts for only 28%7. Evaluations in the GBD Scheme showed that AAP greatly affects mortality more than any other important modifiable factor, including low physical activity and elevated cholesterol and sodium diets50. Numerous manifestations of CVD are related to air pollution, including arterial and venous circulation. Air pollution exposure additionally appears to assume a significant part in disease progression. Incredibly, there is ample evidence of PM's adverse effects on cardiovascular health compared to gaseous pollutants51. Significant effects of PM 2.5 were obtained from long-term exposure that affects mortality from CVD52. The risk of CVD following exposure to PM2.5 was higher in men, the elderly, and those with hypertension, diabetes, heart disease, or background of stroke53. Findings of the Thurston et al. study reported that PM2.5 exposure for a long course increases total risk and CVD risk in this cohort of subjects54. Some studies mention the rapid effect of exposure to air pollutants on the cardiovascular system53,55,56. The apparent link between air pollution and cardiovascular failure's systematic review and meta-analysis demonstrated that the transient rise in gas and particulate components was positively associated with hospitalization risk or death from congestive heart failure. People with persistent heart failure, hypertension, and arrhythmias are at a higher risk5. Several links have recently been recorded between out-of-hospital cardiac arrest and air pollution, mainly PM and ozone57.

Air pollution with directly and/or indirectly biological pathways affects CVD. Direct impacts of air pollution give a conceivable clarification to the event of fast cardiovascular reactions. For example, gases with PM 2.5 soluble substances directly pass through the pulmonary epithelium into the bloodstream58 and raise the risk of ventricular fibrillation, myocardial infarction, and cardiac arrest by having a direct but weak effect on ventricular arrhythmogenesis59. PM 2.5, due to its small size, allows reaching the airways and small alveoli. Studies have shown that short-term exposure to PM boosts the rate of proinflammatory mediators in the blood, coagulation, and inhibition of fibrinolytic capacity60,61. Diesel exhaust exposure also causes inflammation within the plaque, changes in vasomotor tone, and inflammatory mediators62.

Among several metabolisms associated with air pollution and CVD mortality, the significant paths are induction of oxidative stress, systemic inflammation, endothelial function, atherosclerotic function, and arrhythmogenesis63. A decrease in PM 2.5 concentrations is associated with a decrease in the progression of Antima-carotid thickness, which indicates biological viability64. High levels of ambient PM2.5 increase plaque load and vascular dysfunction in atherosclerotic mouse models65,66. Therefore, interpreting the positive relationship between PM2.5 exposure and CVD burden may be significant and support the biological association between air pollution exposure and atherosclerosis. On the other hand, investigations on the relationship between air pollution and CVD have yielded clashing outcomes. Several studies have demonstrated significant relevance26,27,28,67,68, while others were unrelated69.

Prevalence of traditional risk factors and CVD mortality

The relationship between CVD mortality in the Iranian population over 50 years and the prevalence of traditional CVD risk factors, including DM2, tobacco use, high BMI, high LDL cholesterol, high SBP, and smoking, are shown in Fig. 10. Results of Spearman correlation analysis, indicated significant relationship and positive correlation between high SBP (p ≤ 0.001, r = 1), high LDL cholesterol (p ≤ 0.001, r = 0.99), high BMI (p ≤ 0.001, r = 0.95), DM2 (p ≤ 0.001, r = 0.92), tobacco use (p ≤ 0.001, r = 0.89) and moderate positive correlation between smoking (p ≤ 0.001, r = 0.62) and tobacco use (p ≤ 0.001, r = 0.55) and the risk of death from CVD. According to the results of our study, DM2, high SBP, high levels of LDL cholesterol, and high BMI were important risk factors for CVD mortality.

CVD's risk assessment in an individual is usually conducted by CVD's traditional risk factors and subsequently anticipated using fully accessible algorithms, such as the Framingham Risk Score (FRS)70. Some of the most common metabolic consequences of fat, such as high blood pressure, diabetes mellitus, dyslipidemia, and obesity, were considered the principal risk factors for CVD (Bays et al., 2021). Also, In past texts, it has been well established that smoking and physical inactivity are among the risk factors for CVD71,72,73,74.

It remains to be seen, despite the widespread exposure to AAP and the relationship between AAP and traditional CVD risk factors, How important is this exposure to ambient air pollution on the prevalence, exacerbation, and mortality of CVD directly or indirectly?

Ambient air pollution exposure and the prevalence of CVD risk factors

The relationship between the prevalence of CVD risk factors in the population over 50 years, including DM2, high SBP, high BMI, high LDL cholesterol, and AAP, was shown in Fig. 11. Analysis Spearman correlation displayed a significant relationship and positive correlation between air pollution and high SBP (p ≤ 0.001, r = 0.89), high LDL cholesterol (p ≤ 0.001, r = 0.87), high BMI (p ≤ 0.001, r = 0.83) and DM2 (p ≤ 0.001, r = 0.77).

There is a reciprocation interaction between air pollution and risk factors of CVD. Simultaneously, air pollutants may exacerbate and constantly stimulate several traditional risk factors75,76. All of which increase the incidence and severity of CVD. Hypertension is a complex disease with unknown causes. The positive relation between hypertension and CVD has been well demonstrated in some potential cohort research in developed and developing countries77,78,79. It influences almost one billion people worldwide and participates significantly in GBD and mortality80. Over recent years, human epidemiological investigations have assessed the relationship between long-term and short-term exposure to air pollution with hypertension and BP levels81,82. Exposure to AAP and potential environmental pollutants, including heavy metals, are associated with the prevalence of hypertension83. Numerous panel studies worldwide have also shown an association between concentrations of PM 2.5, carbon black, and other pollutants with increased BP from a few hours to a couple of days84,85. Perhaps most important is prolonged exposure to PM 2.5 and traffic-related emissions, which may increase chronic hypertension by themselves86. Smoking is additionally associated with high BP and CVD mortality87,88. While distinct evidence indicates that smoking and high BP affect the risk of death from CVD, the mixed impacts of these factors have rarely been examined. In Wold et al. study, It was indicated that systemic hypertension and vasoconstriction because of transient exposure to PM could increase the risk of acute heart failure. Besides, pulmonary and right ventricular diastolic pressures increment with PM exposure, showing the impact of pulmonary vasoconstriction on air pollution that can worsen congestive heart failure89.

Evidence suggests that despite the undeniable impact of poor eating habits with extra calorie intake and low physical activity90, endocrine-disrupting chemicals (EDC) also intervene in insulin secretion to demonstrate the importance of exposure to environmental pollutants on the pathogenesis of diabetes91,92. Air pollution may impair insulin response sensitivity76. In addition to hypertension and diabetes, obesity and overweight can participate in the global burden of chronic diseases such as CVD. Low-level exposures to industrial air pollution can play and be considered an endocrine disruptor in the obesity epidemic93. Obese people with diabetes might be at greater risk for cardiovascular impacts of PM 2.5 exposure7.

Although not all studies confirm a positive correlation between exposure to AAP and the incidence of multifactorial diseases such as diabetes, hypertension, and obesity, public health outcomes indicate the potential risk of air pollution as a pervasive environmental risk factor for hypertension or diabetes57. However, the participatory role of these hemodynamic changes in expanding acute cardiovascular events associated with AAP is unclear94,95. Since the effect of these factors together on heart disease is not fully understood, laboratory studies seem to be useful to determine the mechanism of these effects.

Strengths and limitations

Exposure to AAP is pervasive and occurs in a wide range. We were able to show this relationship to a large extent by considering other influential factors along with air pollution. In many cases, measuring the long-term exposure of each person to any of the air pollutant particles is very difficult and complex, and our use of an ecological study has been able to solve this problem to a large extent. This investigation inspected the relationship between AAP and CVD mortality, environmental exposure and risk factors for CVD (DM2, high BMI, high SBP, high LDL cholesterol), and the relationship between traditional risk factors and CVD prevalence mortality.

However, we know about the limitations of our study. This study is ecological, and the ecological fallacy should not be ignored96,97. The results of our study are the result of one data set and may not be generalizable to all individuals. Outdoor pollution may be approximately similar for residents of an area. However, indoor pollution can be quite different depending on the lifestyle of the people and the different ventilation of the house from one person to another. The GBD Study expresses that indoor air pollution represents 3 million deaths worldwide and is the fourth-highest risk factor for all deaths50. In addition, the cumulative effects of air pollutants should not be ignored. It should not be forgotten that air pollutants are varied during different days and seasons due to the temperature divergence. Personal and occupational exposure to air pollutants in vulnerable populations, particularly people with diabetes, high blood cholesterol, and high BMI could be reduced via simple measures, comprising:

Preference for walking, cycling, and public transport over car or motorcycle,

Avoid walking and cycling on high-traffic streets, especially during busy hours,

Exercising in healthy environments such as parks and gardens,

Considering the limitation of outdoor times during very polluted periods, particularly for infants, the elderly, and those with cardiorespiratory issues.

It is worth mentioning, that aside from preventive actions comprising indoor air purifications, smoking restrictions, newly generated and low emission cars, environmental researchers, have suggested large-scale outdoor devices for purifying urban air98. Burning fossil fuels is not just a significant source of air pollution yet additionally an important source of greenhouse gases. This way, avoiding the utilization of fossil fuels derivatives will have significant advantages for human health in terms of energy production, both through air pollution exposure and climate change.

Conclusion

The present study investigated the relationship between exposure to ambient air pollution and CVD mortality and other risk factors for CVD mortality. Our study findings indicated a significant relationship between ambient air pollution, ambient PM pollution, ambient ozone, and CVD mortality. We showed the relationship between the exposure to AAP (PM, ozone, and total ambient air pollution, Separately) and each of the investigated traditional risk factors of CVD, including DM2, high SBP, high BMI, and high LDL cholesterol. There is strong evidence to support the mechanism of the relationship between AAP and CVD mortality. However, the level of indoor air pollution should not be ignored. Due to the widespread prevalence of air pollution exposure, political interventions to decrease environmental pollution, especially air pollution, can significantly affect CVD health for people. Air pollution should be one of the various significant modifiable risk factors in the prevention and organization of CVD in health and investigation priorities. Our study suggests that more research must be done on the ideal strategies for reducing AAP and the effects of these exposures on the incidence and mortality of CVD and other associated risk factors.

Acknowledgements

The authors sincerely appreciate all those who contributed to this study.

Funding

This work was supported by Shiraz University of Medical Sciences (Grant No. 1397-01-04-18508).

Author information

Authors and Affiliations

1. Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

Samaneh Dehghani & Vahide Oskoei

2. Department of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

Mohebat Vali & Zahra Maleki

3. Department of Environmental Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

Arian Jafarian

4. Department of Environmental Health Engineering, School of Public Health, Research Center for Health Sciences, Institute of Health, Shiraz University of Medical Sciences, Razi Blvd, Kuye-Zahra Ave, Shiraz, 1417653861, Iran

Mohammad Hoseini

Contributions

S.D.: Conceptualization, Methodology, Investigation, Writing. M.V.: Data curation, Formal analysis, Software, Methodology. A.J.: Writing- Reviewing and Editing. V.O.: Writing- Reviewing and Edit. Z.M.: Writing- Reviewing and Editing, Validation. M.H.: Supervision, Resources, Validation, Conceptualization.

Corresponding author

Correspondence to Mohammad Hoseini.

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The authors declare no competing interests.

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Dehghani, S., Vali, M., Jafarian, A. et al. Ecological study of ambient air pollution exposure and mortality of cardiovascular diseases in elderly. Sci Rep 12, 21295 (2022). https://doi.org/10.1038/s41598-022-24653-0
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DOI: https://doi.org/10.1038/s41598-022-24653-0

# data[].attributes.attachment_link.title
Ecological study of ambient air pollution exposure and mortality of cardiovascular diseases in elderly - Scientific Reports

# data[].attributes.attachment_link.description
As an independent risk factor, ambient air pollution can assume a considerable part in mortality and worsening of cardiovascular disease. We sought to investigate the association between long-term exposure to ambient air pollution and cardiovascular disease mortality and their risk factors in Iranian's elderly population.

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Effectiveness of Motivational Interviewing-Enhanced Behavior Therapy for Adolescents With Attention-Deficit/Hyperactivity Disorder: A Randomized Community-Based Trial.Margaret H Sibley et al.J Am Acad Child Adolesc Psychiatry. 2021 Jun;60(6):745-756.

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Effectiveness of Motivational Interviewing-Enhanced Behavior Therapy for Adolescents With Attention-Deficit/Hyperactivity Disorder: A Randomized Community-Based Trial.Margaret H Sibley et al.J Am Acad Child Adolesc Psychiatry. 2021 Jun;60(6):745-756.

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ENLACE DE ESTUDIO:  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907265/

Este estudio es un ensayo comunitario dado que la población de tratamiento no son las personas, sino un grupo de adolescentes con desorden por déficit de atención e hiperactividad.
Teniendo en cuenta que ésta enfermedad de adolescentes, se considera originada en situaciones sociales vividas por los jóvenes, este es el estudio más idóneo para su realización.
En el caso de estos jóvenes se evalúo el apoyo diario de la autonomía de los pacientes versus cuidado estándar, en búsqueda de mejoría en: la falta de atención, la evolución académica, la funcionalidad familiar y el seguimiento disciplinario.
Este estudio evalúo 4 comunidades pan latinas y pan caribeñas, solo 278 adolescentes. Se confirma en este caso que la debilidad del tipo de estudio comunitario es que su población suele ser pequeña por la dificultad para evaluar de forma homogéneas muchas comunidades a la vez.

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Affiliations

¹ University of Washington School of Medicine, Seattle Children's Research Institute, Seattle; Florida International University Herbert Wertheim College of Medicine, Miami, FL. Electronic address: margaret.sibley@seattlechildrens.org.

² Florida International University, Miami.

Free PMC article

Randomized Controlled Trial

Free PMC article

Affiliations

¹ University of Washington School of Medicine, Seattle Children's Research Institute, Seattle; Florida International University Herbert Wertheim College of Medicine, Miami, FL. Electronic address: margaret.sibley@seattlechildrens.org.

² Florida International University, Miami.

Abstract

Objective: This study tests the effectiveness of parent-teen psychotherapy for adolescent attention-deficit/hyperactivity disorder (ADHD) (Supporting Teens' Autonomy Daily [STAND]) versus usual care (UC) in 4 community clinics.

Method: A randomized clinical trial was conducted with double randomization of adolescents and therapists to STAND versus UC. Participants were 278 culturally diverse adolescents diagnosed with DSM-5 ADHD at baseline and 82 community therapists. Seven primary outcomes were assessed at baseline (BL), posttreatment (PT; mean = 5.11 months post-BL, SD = 2.26), and follow-up (FU; mean = 9.81 months post-BL, SD = 2.50): inattention (IN; parent/teacher-rated), academics (parent-rated/official records), family functioning (parent/adolescent-rated), and disciplinary records. Treatment engagement indicated consumer fit (eg, number or sessions received, percentage of sessions attended by parent, satisfaction). The impact of treatment on concurrent medication use was also examined. Service delivery features were examined as moderators of outcome.

Results: Intent-to-treat (N = 278) analyses indicated no significant group × time effects. STAND only led to superior outcomes when therapists were licensed (22% of sample) versus unlicensed (parent-rated IN: p < .001, d = 1.08; parent-rated academic impairment: p = .010, d = 1.17). Compared to UC, STAND was associated with greater parent participation (p < .001, d = 0.88) and higher scores on certain indices of parent satisfaction. STAND also was associated with superior medication engagement over time compared to UC (odds ratio = 7.18).

Conclusion: Evidence-based psychosocial treatment for adolescent ADHD did not outperform UC on outcome trajectories despite improving some indices of treatment engagement. STAND requires additional adaptation for community contexts.

Clinical trial registration information: STAND Community Trial (STAND); https://clinicaltrials.gov/; NCT02694939.

Keywords: ADHD; adolescence; community-based treatment; psychotherapy.

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Association between caffeine intake and lumbar spine bone mineral density in adults aged 20-49: A cross-sectional study. Gaoxiang Wang et al. Front Endocrinol (Lausanne). 2022 Oct 17;13:1008275. doi: 10.3389/fendo.2022.1008275. eCollection 2022.

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Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital Affiliated to Nanjing University of Chinese Medicine, Shenzhen, China

Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China

The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China

Background: Many epidemiological studies have investigated the connection between coffee intake and bone mineral density (BMD), but the results are controversial. This study aimed to assess the association between caffeine consumption and lumbar BMD in adults aged 20-49.

Methods: From a cross-sectional study based on a large sample of the National Health and Nutrition Examination Survey 2011-2018. After controlling for confounders, the weighted multivariate linear regression model was created and stratified by age, gender, and race for subgroup analysis. In addition, we simultaneously stratified analysis by age and sex and divided caffeine intake into quartiles to assess the association between coffee intake and BMD.

Results: Caffeine intake was not significantly linked with lumbar BMD in this study of 7041 adults. In subgroup studies stratified by age, there was a significant correlation between lumbar BMD and caffeine consumption in participants aged 30-39 and 40-49. In females, there was a positive correlation between lumbar BMD and coffee consumption stratified by gender. When evaluated by race, the association between lumbar BMD and caffeine intake was independent of race. Consequently, when stratifying for age, sex, and coffee intake quartiles, a significant positive correlation was discovered between the fourth coffee intake quartile and lumbar BMD in females aged 30-39. In addition, a negative correlation was discovered between coffee consumption and lumbar BMD in males aged 40-49.

Conclusions: Our research indicates that drinking coffee may benefit 30-39 women's lumbar BMD, but it may adversely affect men aged 40-49.

Introduction

Osteoporosis (OP) is a degenerative disease of the bones that results in weakened bones, weakened microarchitecture, increased fragility, and increased fracture risk ( 1, 2). Owing to the development of an aging population, osteoporosis has become the most common bone-related chronic disease and the bone metabolic disease with the highest incidence. According to a worldwide survey by the International Society for Clinical Densitometry and the International Foundation for Osteoporosis, more than 70 million Americans will be diagnosed with osteoporosis or bone loss by 2030 ( 3). The economic burden of osteoporosis-related fractures is significant, costing approximately $17.9 billion annually in the United States ( 4). Therefore, clinical attention should be focused on identifying modifiable osteoporosis risk factors, such as coffee drinking.

Coffee is one of the most widely consumed beverages in the world nowadays. According to a survey conducted by the National Coffee Association, roughly 64% of adults in the United States drink coffee daily, and approximately 517 million cups of coffee are consumed daily ( 5). Therefore, researchers pay more attention to the effect of caffeine on human health. Epidemiological research ( 6- 11) indicates that coffee consumption can prevent or decrease the risk of cardiovascular disease, chronic liver conditions, neurodegeneration, and cancer. However, coffee consumption can also adversely affect the human body, such as sleep disturbance, anxiety, and poor pregnancy outcomes ( 12). Coffee can significantly affect metabolic levels in adults and has been proven in numerous studies to affect metabolic diseases such as obesity and diabetes significantly ( 13- 16).

In the past, a great deal of epidemiological research has been carried out in order to investigate the connection between coffee consumption and BMD. However, the conclusions have been inconsistent. In a Taiwanese longitudinal study, Chang et al. found drinking coffee to have a significantly beneficial relationship with BMD in both males and premenopausal women ( 17). However, Hallstrom et al. observed that high coffee intake in middle-aged and elderly Swedish women decreased BMD by 2%-4% compared to low coffee intake ( 18). It is puzzling that Demirbag et al. investigated 200 premenopausal individuals and found no correlation between coffee consumption and BMD ( 19). These contradictory results may be attributable to their demographic traits, small sample size, bias in data collection, and other aspects. Therefore, we used the National Health and Nutrition Examination Survey (NHANES) database from 2011 to 2018 to conduct a large-scale, broadly representative clinical study on the connection between coffee consumption and BMD to guide clinicians.

Methods

Data source and study population

This study is based on 2011-2018 NHANES data. The NHANES is a nationally representative sample database that assesses the physical and mental well-being of adults and children in the United States. The NHANES has a complicated, multi-stage stratified sample design that covers individuals from various life backgrounds and is representative of the population as a whole. In addition to demographic, socioeconomic, and nutritional questions, the survey also includes physiological measurements and laboratory tests. The information collected by NHANES is used by public health officials, legislators, and clinicians to estimate how common chronic diseases are and to create good public health policies, public health initiatives, and services that protect the health of the population.

We retrieved a total of 39,156 participants from the 2011-2018 NHANES database, and we excluded 11378 subjects older than 49 years and 16,539 subjects younger than 20. Ultimately, 7041 participants were included in our investigation after we eliminated 5493 adults who had missed two 24-hour dietary recall interviews about caffeine use (n = 2869) or lumbar BMD (n = 1329)( Figure 1).

Figure 1 Flowchart of participants selection.

Ethics statement

NHANES requires all survey participants to sign an informed consent form, which is evaluated and authorized by the National Center for Health Statistics Ethics Review Board. After privacy has been protected, the data are now available to the public. It is already feasible to convert data into an analyzed format. All statistics will be used for research methodology, and all research will comply with applicable laws and standards as long as we follow the research's data usage rules.

Covariates

In this study, we used two 24-hour dietary recall interviews to determine how much caffeine each participant drank daily. The first 24-hour dietary recall interview was conducted in person at the Mobile Examination Center (MEC), and the second 24-hour dietary recall interview was conducted by phone 3-10 days after the MEC. All participants were required to complete both interviews. The subjects were evaluated using dual-energy X-ray absorptiometry (DXA), performed on a Hologic Discovery Model A densitometer (Hologic, Inc., Bedford, Massachusetts) using Apex version 3.2 software. The radiographer who performed the evaluations was trained and certified. A whole-body scan was performed, and the subject's BMD was calculated (Containing lumbar spine BMD information but no femoral neck BMD). In the Body Composition Procedure Manual, which may be found on the NHANES website, there is further information regarding the DXA examination protocol. In addition, we incorporated gender, race/ethnicity, educational level, and moderate exercise as categorical variables in this study. Age, BMI, the ratio of family income to poverty, alkaline phosphatase, blood calcium, blood phosphorus, blood uric acid, total cholesterol, triglyceride, glycohemoglobin, blood urea nitrogen, serum creatinine, urinary albumin creatinine ratio, total albumin, average caffeine intake, lumbar BMD are continuous variables. Visit www.cdc.gov/nchs/nhanes/ to learn more about how covariate data were collected, how two 24-hour recall interviews were conducted, and how lumbar BMD outcome variables were measured.

Statistical analyses

All of the estimates in this investigation were computed using sample weights, following recommended by the NCHS. Continuous variables are shown as the Mean ± SD, and the weighted multiple linear regression model was utilized to determine whether there were differences between the various groupings of continuous variables. The chi-square test results were analyzed to see whether or not there was a significant difference between the categorical variable components. The results of the test are reported as %. Following the recommendations provided by Reporting on Observational Studies in Strengthening Epidemiology, three weighted multivariate linear regression models were created to acquire a more comprehensive understanding of the association between coffee consumption and BMD. Model 1 was left untouched. Model 2 has been tweaked to consider age, gender, and race/ethnicity. Model 3 adjusted for all confounders. We did subgroup analyses based on age, gender, and race to get the most out of these data and investigate further the association between coffee consumption and lumbar BMD. The EmpowerStats ( http://www.empowerstats.com) and R ( http://www.r-project.org) were utilized for every statistical analysis. In general, we regarded P < 0.05 as statistically meaningful.

Results

Table 1 provides the weighted characteristics of the study samples, which include demographic and medical characteristics. The research included 7041 subjects, with 3565 males and 3476 females participating. The average age of men was 33.65 ± 8.62 years old, and that of women was 34.42 ± 8.84 years old, and the difference was statistically meaningful. The daily caffeine intake of male participants was 0.15 ± 0.18 g, and that of female participants was 0.13 ± 0.15 g, and the difference was also statistically meaningful. Furthermore, the difference still existed in educational level, ratio of family income to poverty, moderate activity, alkaline phosphatase, blood calcium, total cholesterol, blood uric acid, triglyceride, blood urea nitrogen, blood creatinine, glycohemoglobin, lumbar BMD and total protein. No statistically significant differences were observed between the male and female participants in terms of,race or ethnicity, BMI, blood phosphorus, and the urine albumin creatinine to ratio.

Table 1 Weighted characteristics of the study sample.

Table 2 presents three weighted multivariate linear regression models. In Model 1, without adjustment for variables, there was a statistically negative association between caffeine consumption and lumbar BMD. As for Model 2 with partial adjustment for covariates and model 3 with adjustment for all variables, average caffeine intake and lumbar BMD were linked, but the link was not statistically significant. When stratified by age, average caffeine consumption was positively and significantly associated with lumbar BMD in adults aged 30-39 and 40-49. Average caffeine intake in female adults was significantly positively associated with lumbar BMD when stratified by gender. Coffee intake and lumbar BMD were not associated with race when evaluated by race.

Table 2 Association between average caffeine intake (g/day) and lumbar bone mineral density (g/cm ²).

Table 3 displays the correlation between average caffeine consumption and BMD stratified by age and sex. Caffeine consumption was found to be positively related to lumbar BMD in females aged 30-39 and negatively related to lumbar BMD in males aged 40-49.By further stratifying the average caffeine intake, we studied the relationship between caffeine intake and lumbar bone mineral density and took the lowest quartile of caffeine intake as the control group. The trend between the quartile of average caffeine intake and lumbar BMD remained significant in the two subgroups.Notably, in the subgroup of women aged 30 - 39 years, the fourth quartile was significantly different from the lowest group, but no difference was found among the four quartile in the subgroup of men aged 40 - 49 years.

Table 3 Association between Average caffeine intake (g/day) and lumbar bone mineral density (g/cm ²), stratified by age and gender.

Discussion

Coffee is the most popular beverage in the world. Osteoporosis is a common endocrine and metabolic disease. BMD is one of the most important diagnostic indexes of OP. Many epidemiological studies have been conducted to investigate the connection between coffee consumption and BMD, but the conclusions are controversial ( 17, 18, 20). As a result, we used the NHANES database to perform this extensive, representative cross-sectional study.

From the NHANES 2011-2018, we chose a representative sample of 9041 adults aged 20-49. In subgroups stratified by age, according to our data, a significant correlation existed between the consumption of coffee and lumbar BMD in individuals aged 30-39 and 40-49. In subgroups stratified by gender, we found that association between caffeine intake and bone mineral density is also influenced by gender. The three models failed to find this connection in subgroups stratified by race. Since the association between the amount of caffeine consumed and the BMD of the lumbar spine varies depending on age and gender, we further analyzed and stratified gender and age simultaneously. We found that women aged 30-39 had a significant positive association between coffee consumption and BMD and that in this group. However, in 40-49 years old men subgroup, we found a negative correlation.

The effect of coffee consumption on BMD is controversial as one of the three most popular beverages in the world. In a clinical study of 4066 postmenopausal women, Choi et al. analyzed by multivariate logistic regression, adjusting for all confounding factors, that the highest coffee intake group had a 36% lower prevalence of osteoporosis than the lowest group ( P = 0.015) ( 21). In a prospective study with up to 30 years of follow-up, researchers randomly selected 7495 men aged 46-56 and found that coffee consumption reduced the incidence of hip fractures. Researchers have found that males who drink coffee have a lower risk of fractures ( 22). Similarly, Yu et al. demonstrated in a large, community-based cross-sectional study that moderate coffee consumption decreases the prevalence of osteoporosis in men ( 23). In a recent meta-analysis of approximately 400,000 participants, researchers found that people with high coffee intake had a lower risk of osteoporosis than those with low coffee intake [OR (95% CI): 0.79 (0.65-0.92)] ( 24). A Hong Kong OP study showed that the serum metabolite levels of caffeine were significantly correlated with BMD, which to some extent, confirmed our findings ( 25). As for the potential pathophysiological aspects of the effect of coffee consumption on BMD. In a recent study, Berman et al. showed that caffeine regulates osteoblast/osteoclast differentiation through nonspecific antagonism of adenosine receptors ( 26). Ankita et al. suggested that the physiological release of purine in the extracellular space plays an important role in bone homeostasis, both by acting on membrane receptors directly affecting osteocytes and by synergistic stimulation with some osteoactive hormones ( 27). In addition, researchers also believe that caffeine affects bone metabolism through mechanisms such as regulating calcium and altering the lipid profile ( 28). Consistent with previous studies, we believe that young women who consume coffee can improve their lumbar spine BMD. However, the finding that men aged 40-49 years who drink coffee may have a potential risk of lumbar spine BMD contradicts previous studies, and we did not find an association after stratifying all variables only by sex, so the conclusions of this male-specific study need to be cautiously interpreted.

Nevertheless, there are some concerns with our study. People older than 50 years were not included in this study due to a scarcity of data, resulting in these subjects being excluded from the analysis, which severely limits the possibility of considering the basic endpoint of fragility fracture risk when referring to "bone health." This is one of the major limitations of this study. Because this was a cross-sectional study, it was not possible to determine whether or not there was a causal connection between the use of coffee and lumbar spine BMD. Due to the limitations of the questionnaire, personal eating habits and lifestyles could not be assessed, and the menstrual conditions, sex hormone levels, and drug use of female participants may have affected the study's findings. Levels of bioactive were unknown. The specific mechanism of coffee action is not involved in this study. This study has many covariates, and there may be some collinearity between them. In addition, hip femoral neck BMD was not included in this study due to data limitations. Despite these limitations, it is undeniable that our study's sample size is significant and that it represents a sophisticated, stratified, multi-stage probabilistic sample of the non-institutionalized American population. In terms of survey techniques and quality assurance, NHANES is of high caliber. Additionally, after adjusting for various confounders, we performed weighted multiple linear regression analysis and subgroup analyses stratified by age, gender, and ethnicity to assess the effect of coffee consumption on BMD. Most importantly, the findings of this study provide new information for patients with osteoporosis or low bone mass since they demonstrate that drinking coffee has a beneficial impact on BMD in young women. For future research on this topic, due to the lack of data on people over 50 years of age in this study, we suggest that future studies take more into account factors such as menopause and old age. Considering the limitations and shortcomings of our study, we recommend that more prospective studies be conducted in the future to confirm the causal relationship between caffeine and BMD. In addition, coffee contains various active ingredients, and future studies should fully consider the effects of other minerals and other factors on bone.

In conclusion, according to this study, drinking coffee may benefit women aged 30-39 lumbar BMD, but may negatively affect men aged 40-49. Although our study is focused on caffeine, in our daily life, we also need to pay attention to the differences in the content of minerals, lipids, proteins, and other substances in different coffee powders, which may also have an impact on bone health, although it is difficult to weight them because they are not easy to calculate and consider in observational studies.

Data availability statement

Publicly available datasets were analyzed in this study. The survey data can be found here: www.cdc.gov/nchs/nhanes/.

Ethics statement

NHANES protocols were approved by the Research Ethics Review Board of NCHS, and Written informed consent was obtained from each participant.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Funding

This study was funded by the The Shenzhen Municipal Science and Technology Bureau (No. JCYJ20170817094838619 & JCYJ20180302173821841); National Natural Science Foundation of China (No. 82104759); and The Natural Science Foundation of Guangdong Provincial (No. 2019A1515110108).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

7. Sartini M, Bragazzi NL, Spagnolo AM, Schinca E, Ottria G, Dupont C, et al. Coffee consumption and risk of colorectal cancer: A systematic review and meta-analysis of prospective studies. Nutrients (2019) 11:694. doi: 10.3390/nu11030694

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16. Cherukuri L, Kinninger A, Birudaraju D, Lakshmanan S, Li D, Flores F, et al. Effect of body mass index on bone mineral density is age-specific. Nutrition Metab Cardiovasc Dis (2021) 31:1767-73. doi: 10.1016/j.numecd.2021.02.027

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# data[].attributes.attachment_link.title
Association between caffeine intake and lumbar spine bone mineral density in adults aged 20-49: A cross-sectional study

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BackgroundMany epidemiological studies have investigated the connection between coffee intake and bone mineral density (BMD), but the results are controversial. This study aimed to assess the association between caffeine consumption and lumbar BMD in adults aged 20-49.MethodsFrom a cross-sectional study based on a large sample of the National Health and Nutrition Examination Survey 2011-2018.

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Un estudio descriptivo es aquél en que la información es recolectada sin cambiar el entorno (es decir, no hay manipulación).

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se divide en descriptivos y analíticos

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Reportes de caso

Los reportes de caso son un tipo de estudio en donde el foco del mismo se pone sobre un individuo en particular.

Generalmente son utilizados en la medicina y llevados adelante por un observador que puede ser un médico, el cual detecta una reacción atípica de una enfermedad en un paciente en particular.

Este tipo de estudios son utilizados como primera aproximación en la identificación de nuevas enfermedades, que serán estudiadas más a fondo con otro tipo de investigaciones más completas.

Reportes de serie de casos

Básicamente, los reportes de series de caso son una combinación de reportes de caso. Es decir, es una colección de reportes de situaciones individuales, las cuales tienen el mismo hilo conductor y, además, pertenecen a un período de tiempo similar.

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• Estudios transversales:
intentan analizar el fenómeno en un periodo de tiempo corto, un punto en el tiempo, por eso también se les denomina “de corte”. Es como si diéramos un corte al tiempo y dijésemos que ocurre aquí y ahora mismo. Un estudio que pretendiera conocer la prevalencia de las caries dentales en los escolares de educación primaria de los colegios de la Comunidad Autónoma de Madrid, sería un estudio de este tipo.
• Estudios longitudinales.
Estudio de uno o más factores en un periodo de tiempo más largo. Imaginemos en el caso anterior que no queremos conocer la prevalencia de la caries en el mes de marzo de 2003, sino que la Consejería de Salud la CA de Madrid quiere saber la evolución de la caries en los próximos 10 años, y para ello cuenta con datos sobre la prevalencia a marzo de 2003. Se debe plantear un estudio longitudinal en el tiempo. Otro asunto es el interés o relevancia de este tipo de estudio. A su vez sabemos que los estudios descriptivos también pueden ser:

• Individuales: El típico caso de uno o varios pacientes, que se presenta en una sesión clínica, respondería al modelo de estudio individual, denominado “estudio de casos”.
• Poblacionales: La situación de la caries del epígrafe anterior respondería a un estudio descriptivo poblacional.

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Los estudios Analíticos se caracterizan porque pretenden descubrir una hipotética relación entre algún factor de riesgo y un determinado efecto, es decir, pretenden establecer una relación causal entre dos fenómenos naturales.

En este tipo de estudios, es esencial entender que para que prevalezca su condición de estudio observacional, han de cumplir la premisa de que el investigador no establece ningún tipo de intervención en los grupos de estudio, los cuales se someten a las leyes naturales de evolución desde que interviene la causa hasta que se produce el hipotético efecto resultante.

Los estudios analíticos requieren un diseño especial y más cuidadoso que los estudios descriptivos, sobre todo en lo que se refiere a los sistemas de control de sesgos y de factores de confusión, que de no establecerse desde su diseño inicial de forma correcta podrían invalidar los resultados del estudio.

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En este tipo de estudios se establecen dos cohortes, una se corresponde con la cohorte de estudio y estará compuesta por la población expuesta al hipotético factor de riesgo, y la otra, se comporta como cohorte control, compuesta por individuos que no se encuentren expuestos al hipotético factor de riesgo. Establecidas las cohortes, se realiza un seguimiento en el tiempo de cada una de ellas (población expuesta y población no expuesta), estudiando el comportamiento de la cada una en cuanto a la aparición del efecto o enfermedad o desenlace (incidencia). También se les denomina prospectivos por que van hacia adelante desde la exposición hasta un efecto.

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En los estudios de casos y controles se elige un grupo de individuos que tienen una enfermedad determinada (casos), y otro en el que está ausente. Ambos grupos se comparan respecto a una exposición que se sospecha que está relacionada con dicha enfermedad. La función del grupo control es precisamente estimar la proporción de exposición esperada en un grupo que no tiene la enfermedad.

Lo estudios de Casos y Controles tiene en común con los estudios de Cohortes que también se establecen dos poblaciones. La diferencia estriba en que, en los estudios de Casos y Controles las poblaciones de estudio se establecen en función de la presencia o no del efecto o enfermedad, es decir, el grupo de los casos estaría compuesto por los individuos que presentan la enfermedad o efecto estudio, y el grupo Control por la población que no padece la enfermedad.

En este caso, el estudio no requiere de un seguimiento, sino que su enfoque es retrospectivo, hacia atrás, para estudiar la relación, contacto o exposición previa de cada uno de los grupos (enfermos y no enfermos) con uno o varios hipotéticos factores de riesgo. Generalmente para la reconstrucción de la historia de exposición se recurre a encuestas, revisión de historias clínicas, analíticas, exploraciones, etc.

En definitiva, en un estudio de casos y controles lo que se mide es si la frecuencia del factor de riesgo entre nuestros casos enfermos es superior a la observada en nuestros controles no enfermos.

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Rabdomiólisis severa asociada a atorvastatina. Reporte de casoJorge Medina-Romero. Rev Med Inst Mex Seguro Soc. 2023 Mar-Apr; 61(2): 245–250.

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Rabdomiólisis severa asociada a atorvastatina. Reporte de casoJorge Medina-Romero. Rev Med Inst Mex Seguro Soc. 2023 Mar-Apr; 61(2): 245–250.

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ENLACE DE ESTUDIO: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10395881/

Este artículo publicado nos muestra un estudio observacional, descriptivo tipo reporte de caso. Es una publicación interesante dado que es muy rara la presencia de rabdomiólisis asociada a uso de estatina.
Este es el tipo de estudio más simple que hay, no busca hacer asociaciones entre variables, sino solo describir; siendo ésta su mayor debilidad.
Pueden ser usados como base para la generación de estudios analíticos.

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Rabdomiólisis severa asociada a atorvastatina. Reporte de caso

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la dislipidemia es un factor de riesgo para el desarrollo de ateroesclerosis y cardiopatía isquémica. Las estatinas son fármacos seguros que forman parte del tratamiento de rutina en el paciente con infarto agudo de miocardio (IAM).…

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Thyroid cancer and its associated factors: A population-based case-control studyMohammad Taher Parad et al. Int J Cancer. 2021 Aug 1;149(3):514-521

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Thyroid cancer and its associated factors: A population-based case-control studyMohammad Taher Parad et al. Int J Cancer. 2021 Aug 1;149(3):514-521

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ENLACE DE ESTUDIO: https://onlinelibrary.wiley.com/doi/10.1002/ijc.33537

Éste estudio trata sobre cáncer de tiroides, una enfermedad muy frecuente que cumple criterios de prevalencia para ser evaluada por el tipo de estudio casos y controles.
Este es un estudio longitudinal.
Esta publicación basó su evaluación en un cuestionario practicado por personal de salud por lo tanto, tiene en cuenta variables que ocurrieron antes y despúes del evento de interés, como se describe en este tipo de estudios.
El tipo de estudio de casos y controles evalúa casos nuevos, incidentes, por lo tanto en este caso se excluyó pacientes con recidivas.
Esta publicación como es esperado en los estudios de casos y controles que se basan en cuestionarios, tiene el sesgo del recuerdo, así como el sesgo de pérdida del seguimiento por cambio de dirección o teléfono. Este estudio ofrece buena información sobre variables que se relacionan con mayor o menor riesgo de cáncer de tiroides

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Interaction of sleep duration and depression on cardiovascular disease: a retrospective cohort study. Bowen Jin, et al. BMC Public Health. 2022 Sep 15;22(1):1752.

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Interaction of sleep duration and depression on cardiovascular disease: a retrospective cohort study. Bowen Jin, et al. BMC Public Health. 2022 Sep 15;22(1):1752.

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ENLACE DE ESTUDIO: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-022-14143-3

Este ejemplo de estudio de cohorte, es considerado un estudio longitudinal retrospectivo porque ante la disponibilidad de datos de la base CHARLS, se analizaron datos en 2018 que fueron tomados en 2015, pero como explica la teoría en el estudio de cohorte se está buscando el desenlace de forma prospectiva, hacia adelante.
Este es el mejor tipo de estudio para evaluar las causas de una enfermedad y cuantificar el riesgo de desarrollo de la enfermedad.
El estudio de cohorte tiene seguimientos largos, en este caso desde 2011 hasta 2018.
La enfermedad cardiovascular es perfecta como desenlace para las cohortes porque tiene alta prevalencia y permite recolección más rápida de los casos de seguimiento, sin embargo se puede usar bases de datos que facilitan el trabajo como la descrita en este estudio: CHARLS.

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BMC Public Health 22, Article number: 1752 (2022) Cite this article

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Abstract

Background

To assess the interaction of sleep duration and depression on the risk of cardiovascular disease (CVD).

Methods

A total of 13,488 eligible participants were enrolled in this retrospective cohort study eventually. Baseline characteristics were extracted from the China Health and Retirement Longitudinal Study (CHARLS) database, including age, sex, diabetes, high-density lipoprotein (HDL), blood glucose (GLU), glycosylated hemoglobin (GHB) etc. Univariate and multivariate negative binomial regression models were carried out to assess the statistical correlation of sleep duration and depression on CVD separately. Additionally, multivariate negative binomial regression model was used to estimate the interaction of sleep duration and depression on CVD risk.

Results

After adjusting for age, sex, educational background, hypertension, diabetes, dyslipidemia, the use of hypnotics, disability, nap, drinking, deposit, sleep disturbance, HDL, triglyceride, total cholesterol, GLU and GHB, the risk of CVD in participants with the short sleep duration was increased in comparison with the normal sleep duration [relative risk (RR)=1.02, 95% confidence interval (CI):1.01-1.03]; compared to the participants with non-depression, participants suffered from depression had an increased risk of CVD (RR=1.05, 95%CI:1.04-1.06). Additionally, the result also suggested that the interaction between short sleep duration and depression on the risk of CVD was statistically significant in these patients with diabetes and was a multiplicative interaction.

Conclusion

An interaction between short sleep duration and depression in relation to an increased risk of CVD among Chinese middle-aged and elderly individuals was noticed, which may provide a reference that people with diabetes should focus on their sleep duration and the occurrence of depression, and coexisting short sleep duration and depression may expose them to a higher risk of CVD.

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Background

Cardiovascular disease (CVD), as a common chronic disease, is still the main cause of global mortality and disability [ 1, 2]. In recent years, the incidence of CVD has remained a steady rise globally, reaching 523 million in 2019 [ 2]. It is estimated that there was 17.9 million people died of CVD every year, accounting for 32% of global deaths [ 3], brought huge burden of disease for many families. As a consequence, it is very important for closely paying attention to risk factors to prevent the occurrence of CVD.

To date, several studies have reported that poor behavior and mental health are closely associated with the CVD risk, including short sleep duration, long sleep duration, and depression [ 4, 5]. A systematic review and meta-analysis showed that both short and long sleep duration were markers of cardiovascular outcomes, and were also associated with a higher risk of coronary heart disease (CHD) [ 6]. In addition, Yin, et al. also pointed out that there was a U‐shaped association between sleep duration and risk of CVD, and insufficient or excessive sleep duration were significantly related to an elevated risk of CVD [ 7]. Depression as a mental illness of low mood and loss of interest, has become increasingly common worldwide [ 8]. A growing body of scientific evidence have evaluated the role of depression in the development of CVD [ 8, 9]. In the study of Carney, et al., the result showed that depression was recognized as a highly prevalent risk factor for CHD occurrence [ 10]. The association mechanism of depression and CVD risk might be associated with the vascular endothelial dysfunction and increased platelet aggregation among patients with depression, thus accelerating the development of CVD [ 11]. Notably, there were some studies have showed a bidirectional relationship of sleep duration and depression [ 12, 13]; insufficient or excessive sleep duration could increase the risk of depression [ 12]. Simultaneously, people with depression could bring a short sleep duration [ 13]. Although short/long sleep duration and depression have been considered as risk factors for the development of CVD, people with combined short/long sleep duration and depression may represent a population with a higher risk of CVD due to a possible interaction of short/long sleep duration and depression. There were few studies, to our knowledge, have assessed the influence of the coexistence of short/long sleep duration and depression with regard to the CVD risk to date among middle-aged and elderly people.

Herein, in this study, we attempted to investigate the association between short/long sleep duration, depression and the risk of CVD based on the China Health and Retirement Longitudinal Study (CHARLS) database, and evaluate a joint effect of short/long sleep duration and depression on the CVD risk.

Methods

Data sources

All data in this retrospective cohort study were obtained from the CHARLS database [ 14], which is a nationally representative investigation of Chinese adults with 45 years or older. The investigation aimed at assessing the social, economic and health circumstances of residents. Respondents were followed every 2-3 years by conducting face-to-face computer-assisted personal interviews, physical measurements and blood tests. The baseline survey was carried out in 2011, with three follow-up surveys conducted in 2013, 2015, and 2018 [ 15, 16]. http://charls.pku.edu.cn/

Study eligibility criteria

Due to the high rate of lost follow-up for the included population of CHARLS database before 2015, in this retrospective cohort study, we chose the baseline data in the CHARLS database 2015, and follow-up data in 2018. Included criteria: participants had information about sleep duration and depression in the CHARLS database 2015 ( n=14,962). Excluded criteria: participants already diagnosed with CVD before survey in 2015 (Fig. 1). All interviewees in CHARLS database needed to sign informed consent, and Biomedical Ethics Review Committee of Peking University approved the ethical review for the data collection in CHARLS database [ 14], thus according to the Ethics Review Committee of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, secondary database analysis has been exempted from an ethical review.

Flow chart of participants. 4253 participants had missing data and were treated with multiple imputation

Data collection

Baseline variables and laboratory indicators were collected, including age (years), sex, educational background, marital status, deposit (CN¥), disability, exercise time (h/day), drinking, smoking, sleep time (h/day), depression, nap (min/day), chronic kidney disease (CKD), dyslipidemia, sleep disturbance, the use of hypnotics, diabetes, CVD, triglyceride (TG, mg/dl), high-density lipoprotein (HDL, mg/dl), low-density lipoprotein (LDL, mg/dl), systolic blood pressure (SBP, mmHg), diastolic blood pressure (DBP, mmHg), total cholesterol (TC, mg/dl), blood glucose (GLU, mg/dl), glycosylated hemoglobin (GHB, %).

Sleep duration was assessed by the respondents' self-reported question which asked, "During the past month, how many hours of actual sleep did you get at night (average hours for one night)? This may be shorter than the number of hours you spend in bed." The short, normal and long sleep duration were defined as <6 h, 6-8 h, >8 h, respectively [ 17]. Nap duration was measured by the following question "During the past month, how long did you take a nap after lunch on average?" (0 represent that respondent did not nap duration) [ 14]. Sleep disturbance was defined as how many days a week did participants have trouble falling asleep, frequently nighttime awakenings and earlier waking [ 18]: rarely or none of the time (<1 day), some or a little of the time (1-2 days), occasionally or a moderate amount of the time (3-4 days), and most or all of the time (5-7 days). The Epidemiological Studies Depression Scale (CES-D) was used to assess depression, which has been used to measure depression of the population [ 19]. The scale options consisted of 4 levels and were assigned: "rarely or none of the time=0", "some or few times=1", "occasionally or moderate number of times=2", "most or all of the time=3"; The total score ranges from 0 to 30, with a scores ≥10 were defined as having depression [ 20]. Hypertension, CKD, dyslipidemia and diabetes was assessed by a self-report of physician's diagnosis: Have you been diagnosed with hypertension, CKD, dyslipidemia or diabetes by a doctor? Participants who answered "yes" to the question were defined as having hypertension, CKD, dyslipidemia or diabetes [ 21].

Outcomes

Outcome variable was defined as the occurrence of CVD in the present study. The CVD was assessed by the following questions: "Have you been told by a doctor that you have been diagnosed with a stroke" or "Have you been diagnosed with heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems?" Participants who answered "yes" to the question during the follow-up period were defined as having CVD [ 22].

Statistical analysis

The normality test of measurement data was conducted by Shapiro-Wilk, normal distribution data was exhibited as mean ± standard deviation (Mean ± SD), and comparison between groups adopted independent sample t-test and ANOVA was used for comparison between multiple groups. Non-normal data were described in terms of

median and interquartile range [M (Q1, Q3)], and the comparison between groups was performed by Mann-Whitney U test and Kruskal-Wallis H test was used for comparison between multiple groups. The enumeration data were expressed as number of cases and composition ratio n (%), Chi-square or Fisher's exact test was used for comparison between two groups.

We adopted the univariate negative binomial regression model to explore the possible covariates that were associated with CVD. Then, multivariate negative binomial regression model was carried out to assess the statistical correlation of sleep duration and depression on CVD separately. Three models were used in this study. Model 1 was regarded as unadjusted; Model 2 adjusted several covariates that were performed for statistically significant in univariate analysis and had an impact on CVD in the literature, including age, sex, educational background, marital status, exercise time, chronic kidney disease, hypertension, diabetes, dyslipidemia, the use of hypnotics, disability, nap, drinking and deposit; Model 3 adjusted age, sex, educational background, marital status, exercise time, chronic kidney disease, hypertension, diabetes, dyslipidemia, the use of hypnotics, disability, nap, drinking, deposit, sleep disturbance, HDL, TC, TG, GLU and GHB. Additionally, we used the multivariate negative binomial regression models to evaluate the joint effect of sleep duration and depression on the CVD risk in different populations. Relative risk (RR) with 95% confidence interval (CI) was reported. With respect to missing data of the variables, we adopted multiple interpolation method. The data were interpolated for five times, and five datasets were generated. In the five datasets, the mean of the data with five times interpolations was taken for measurement data, and the mode of the data interpolated for five times was taken for enumeration data. A new interpolated dataset was obtained for subsequent analysis. Sensitivity analysis of missing data before and after interpolation was shown in Supplemental Table 1. Smoking data was missing too much and not participated in the analysis. We used the SAS (version 9.4, SAS institute., Cary, NC, USA) software for the statistical analysis and R (version 4. 0. 3, Mice package) for the multiple interpolation. Statistical tests were performed by using bilateral tests. P<0.05 was regarded as statistically significant.

Results

Baseline characteristics

After excluded some participants who were diagnosed with CVD before survey ( n=329), and we also excluded 1,145 participants did not record whether CVD occurred at the end of the follow-up. A total of 13,488 eligible participants were enrolled in this retrospective cohort study eventually, with an average follow-up time of 2.7 years. There are 1,563 (11.59%) incident cases of CVD identified at the follow-up period to 2018. All participants' characteristics were shown in Table 1. The study subjects' average age was 57.89 ± 9.87 years. Furthermore, 3,772 (27.97%) participants had short sleep duration and 1,231 (9.13%) had long sleep duration, 4,091 (30.33%) had depression. It is worth noting that the population proportion of CVD occurrence among short sleep duration was higher than normal and long sleep duration groups, and the CVD occurred more frequently in the depression group than the non-depression group. Detailed baseline information was given in Table 1.

Effect of sleep duration/ depression on CVD

Some possible variables that were associated with CVD were shown in Table 2 ( P<0.05) by univariate negative binomial regression model. The effects on CVD of sleep duration were presented in the Table 3. Model 1 (RR=1.03, 95%CI:1.02-1.04) showed that the risk of CVD in the short sleep duration group was increased in comparison with the normal sleep duration group, with similar results in Model 2 (RR=1.02, 95%CI:1.01-1.03) and Model 3 (RR=1.02, 95%CI:1.01-1.03). While the results of Model 1, Model 2 and Model 3 demonstrated that there was no significant difference between long sleep duration group and CVD ( P>0.05).

As presented in Table 3, the results of three models indicated the effects of depression on the risk of CVD. Compared with non-depression group, depression group had a 0.06-fold (Model 1: RR=1.06, 95%CI:1.05-1.07), 0.05-fold (Model 2: RR=1.05, 95%CI:1.04-1.06), and 0.05-fold (Model 3: RR=1.05, 95%CI:1.04-1.06) increased risk of CVD.

The interaction between short sleep duration and depression on CVD in different populations

After incorporating short sleep duration, depression and the interaction term of short sleep duration and depression into multifactor negative binomial regression model, we found that the interaction between short sleep duration and depression on CVD was statistically significant in these patients with diabetes and was a multiplicative interaction ( P<0.05, Table 4). However, with respect to the relationship between short sleep duration and depression on CVD for total population or hypertension population, no an interaction was observed ( P>0.05, Table 4).

Discussion

In this analysis of 13,488 participants from CHARLS database, we revealed that short sleep duration and depression were independent risk factors for CVD occurrence; Importantly, we found that there might be an interaction between short sleep duration and depression in relation to an increased risk of CVD among middle-aged and elderly patients with diabetes.

For the present study, after adjusted covariates, the risk of CVD in people with independent short sleep duration and depression was 0.02 times and 0.05 times than those with normal sleep duration and without depression, respectively. There was no doubt that our result showed that short sleep duration and depression were associated with the increased risk of CVD, which were mostly in line with prior researches [ 9, 23, 24, 25]. Short sleep duration was associated with an increased levels of markers of inflammation, [ 26]. When short sleep duration triggered mild inflammation, leading to an increased stress response in the hypothalamic-pituitary-adrenal axis, which may cause the rise of blood pressure and an increased risk of CVD [ 26]. Not only that, short sleep duration could induce biological effects including the changes in neural autonomic control and coagulation responses, an elevated level of oxidative stress, and accelerated atherosclerosis, triggering metabolic disorders to raise the risk of CVD [ 25]. Likewise, the associated mechanisms of depression and CVD might be related to endothelial dysfunction, autonomic nerve dysfunction, inflammation and life behavior [ 27, 28]. To our knowledge, some studies also reported a link between long sleep duration and increased risk of CVD among elderly people, which might be associated with arterial stiffness, blood pressure variability, gluco-regulatory function and systemic inflammation [ 29, 30]. However, our study showed that there was no statistically difference between long sleep duration group and CVD risk among Chinese middle-aged and elderly individuals [ 31], and the reason may be due to the difference of sample size. Simultaneously, we also found that there were 9.13% Chinese middle-aged and elderly individuals with long sleep duration, and more studies are still warranted on this relationship of long sleep duration and CVD risk in the future.

For the present study, the interaction between short sleep duration and depression on CVD risk for total population was not observed. However, we found that the interaction between short sleep duration and depression might be associated with an increased risk of CVD for middle-aged and elderly patients with diabetes. In other words, when patients with diabetes suffered from both of symptom of short sleep duration and depression, there was a higher risk of CVD. Nowadays, diabetes has been considered as one of the most common chronic conditions, and its prevalence are increasing worldwide [ 32]. Previous studies have suggested that people with diabetes appear to be at greater risk of depression [ 32, 33, 34]. In addition, some studies have shown that people with both diabetes and depression could suffer poorer outcomes, such as poorer quality of life, poorer self-management of diabetes and poorer medical outcomes [ 35, 36], which also suggested an importance of paying attention to the prognosis of patients with diabetes and depression. Additionally, insufficient sleep duration was also highly prevalent in patients with diabetes [ 37], which may contribute to a poor prognosis in those patients. In our study, coexisting short sleep duration and depression may increase the risk of CVD in middle-aged and elderly patients with diabetes. Accordingly, this finding may support the viewpoint that, patients with diabetes should pay attention to their sleep duration and the occurrence of depression. Appropriate increase of sleep duration and physical activities, a healthy diet and psychological treatment may beneficial to prevent the risk of CVD in middle-aged and elderly patients with diabetes [ 38, 39]. Although we found an interaction between depression and sleep duration on the risk of CVD in middle-aged and elderly patients with diabetes, more prospective studies are needed in the future to validate our results and explore the possible mechanism.

The strengths of our study included a large sample size, make the findings more convincing; and the results also may provide a reference that with respect to patients with diabetes, they should pay more attention to both the sleep time and the occurrence of depression, to decrease the risk of CVD. There are limitations that cannot be ignored. Firstly, the issue whether eligible patients diagnosed as short/long sleep duration or depression have been treated not considered in the present study, which may not be got from CHARLS database. Secondly, the coexistence duration of short sleep duration and depression may influence risk of CVD, there was no information collected from CHARLS database about the duration of both short sleep duration and depression, and more trials still are needed to confirm this association. Thirdly, CVD was defined as outcome variable, contained heart attack, coronary heart disease, angina pectoris, congestive heart failure or other heart problems and stroke, but we don't know is that the synergistic interaction between short sleep duration and depression increase the higher risk for what kind of diseases. Fourthly, smoking has long been considered an important risk factor for CVD [ 40]. But, in this study, the variable (smoking) was missing so much that we excluded it. This is a limitation of our study. Lastly, short observational period for observation the incidence of CVD needs to be noted in this study, and more prospective studies with long follow-up periods need to be conducted in the future to verify our results.

Conclusion

In short, we found an interaction between depression and short sleep duration on the risk of CVD among middle-aged and elderly patients with diabetes. Patients with diabetes should pay more rigorous attention to their sleep duration and the occurrence of depression, and coexisting short sleep duration and depression may expose them to a higher risk of CVD. However, more researches are needed to confirm this association in the future.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the CHARLS repository, http://charls.pku.edu.cn/.

Abbreviations

CVD:

Cardiovascular disease

CHARLS:

China Health and Retirement Longitudinal Study

TG:

Triglyceride

HDL:

High-density lipoprotein

LDL:

Low-density lipoprotein

SBP:

Systolic blood pressure

DBP:

Diastolic blood pressure

TC:

Total cholesterol

GLU:

Glucose

GHB:

Glycosylated hemoglobin

CES-D:

Epidemiological Studies Depression Scale

Mean ± SD:

Mean ± standard deviation

M (Q1, Q3):

Median and interquartile range

Funding

This study was supported by the Scientific and Technological Innovation Foundation of China Academy of Chinese Medicine Sciences (No. CI2021A04306) and Beijing Natural Science Foundation (No. 7222315).

Author information

Author notes

Bowen Jin and Hang Zhang contributed equally to this study.

Authors and Affiliations

1. Department of Cardiac Surgery, Wuhan Asia Heart Hospital, Wuhan, 430022, Hubei, P.R. China

Bowen Jin & Hang Zhang

2. Beijing Union University, Beijing, 100101, P.R. China

Fuchun Song

3. Immunology Laboratory, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 Beixiange, Xicheng District, Beijing, 100053, P.R. China

Guangjun Wu & Hui Yang

Contributions

BJ, HZ and HY designed the study. BJ and HZ wrote the manuscript. FS and GW collected, analyzed and interpreted the data. HY critically reviewed, edited and approved the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hui Yang.

Ethics declarations

Ethics approval and consent to participate

This research analyzed de-identified information downloaded from CHARLS database, which is exempt from Institutional Review Board approval of Guang'anmen Hospital, China Academy of Chinese Medical Sciences. All methods were carried out in accordance with relevant guidelines and regulations. Written Informed Consent was obtained from all subjects.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Jin, B., Zhang, H., Song, F. et al. Interaction of sleep duration and depression on cardiovascular disease: a retrospective cohort study. BMC Public Health 22, 1752 (2022). https://doi.org/10.1186/s12889-022-14143-3
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DOI: https://doi.org/10.1186/s12889-022-14143-3

Keywords

CHARLS

Sleep duration

Depression

CVD

Interaction

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Interaction of sleep duration and depression on cardiovascular disease: a retrospective cohort study - BMC Public Health

# data[].attributes.attachment_link.description
Background To assess the interaction of sleep duration and depression on the risk of cardiovascular disease (CVD). Methods A total of 13,488 eligible participants were enrolled in this retrospective cohort study eventually. Baseline characteristics were extracted from the China Health and Retirement Longitudinal Study (CHARLS) database, including age, sex, diabetes, high-density lipoprotein (HDL), blood glucose (GLU), glycosylated hemoglobin (GHB) etc.