Examining relationships between perceived neighborhood social cohesion and ideal cardiovascular health and whether psychosocial stressors modify observed relationships among JHS, MESA, and MASALA participants

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Abstract

Background

Psychosocial stressors increase the risks for cardiovascular disease across diverse populations. However, neighborhood level resilience resources may protect against poor cardiovascular health (CVH). This study used data from three CVH cohorts to examine longitudinally the associations of a resilience resource, perceived neighborhood social cohesion (hereafter referred to as neighborhood social cohesion), with the American Heart Association’s Life’s Simple 7 (LS7), and whether psychosocial stressors modify observed relationships.

Methods

We examined neighborhood social cohesion (measured in tertiles) and LS7 in the Jackson Heart Study, Multi-Ethnic Study of Atherosclerosis, and Mediators of Atherosclerosis in South Asians Living in America study. We used repeated-measures, modified Poisson regression models to estimate the relationship between neighborhood social cohesion and LS7 (primary analysis, n = 6,086) and four biological metrics (body mass index, blood pressure, cholesterol, blood glucose; secondary analysis, n = 7,291). We assessed effect measure modification by each psychosocial stressor (e.g., low educational attainment, discrimination).

Results

In primary analyses, adjusted prevalence ratios (aPR) and 95% confidence intervals (CIs) for ideal/intermediate versus poor CVH among high or medium (versus low) neighborhood social cohesion were 1.01 (0.97–1.05) and 1.02 (0.98–1.06), respectively. The psychosocial stressors, low education and discrimination, functioned as effect modifiers. Secondary analyses showed similar findings. Also, in the secondary analyses, there was evidence for effect modification by income.

Conclusion

We did not find much support for an association between neighborhood social cohesion and LS7, but did find evidence of effect modification. Some of the effect modification results operated in unexpected directions. Future studies should examine neighborhood social cohesion more comprehensively and assess for effect modification by psychosocial stressors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14270-x.

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Most cited references 42

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The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

L Radloff (1977)

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Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019

Gregory A Roth, George A Mensah, Catherine O. Johnson … (2022)

Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases.

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2021 ESC Guidelines on cardiovascular disease prevention in clinical practice

Frank L. J. Visseren, François Mach, Yvo M. Smulders … (2021)

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Author and article information

Contributors

Akilah J. Dulin: akilah_dulin@brown.edu

Journal

Journal ID (nlm-ta): BMC Public Health

Journal ID (iso-abbrev): BMC Public Health

Title: BMC Public Health

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2458

Publication date (Electronic): 11 October 2022

Publication date PMC-release: 11 October 2022

Publication date Collection: 2022

Volume: 22

Electronic Location Identifier: 1890

Affiliations

[1 ]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Center for Health Promotion and Health Equity, , Brown University, ; Providence, RI USA

[2 ]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Center for Epidemiologic Research, Department of Epidemiology, , Brown University, ; Providence, RI USA

[3 ]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Hassenfeld Child Health Innovation Institute, , Brown University, ; Providence, Rhode Island USA

[4 ]GRID grid.266097.c, ISNI 0000 0001 2222 1582, Department of Social Medicine, Population and Public Health, , University of California Riverside School of Medicine, ; Riverside, CA USA

[5 ]GRID grid.214458.e, ISNI 0000000086837370, Department of Epidemiology, , University of Michigan, ; Ann Arbor, MI USA

[6 ]GRID grid.240267.5, ISNI 0000 0004 0443 5079, Centers for Behavioral and Preventive Medicine, The Miriam Hospital, ; Providence, RI USA

[7 ]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Department of Family Medicine, , Warren Alpert Medical School of Brown University, ; Providence, RI USA

[8 ]GRID grid.240223.5, ISNI 0000 0004 0453 0041, Center for Primary Care and Prevention Kent Memorial Hospital, ; Warwick, RI USA

[9 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Division of General Internal Medicine, , University of California, San Francisco, ; San Francisco, CA USA

[10 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Department of Internal Medicine, , Northwestern University, ; Chicago, IL USA

[11 ]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Center for Health Promotion and Health Equity Research, , Brown University School of Public Health, ; Box G-S121-8, 02912 Providence, RI USA

Article

Publisher ID: 14270

DOI: 10.1186/s12889-022-14270-x

PMC ID: 9552445

PubMed ID: 36221065

SO-VID: 736d2ab9-bae5-4b64-a3ed-2d24146db0de

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 10 May 2022

Date revision received : 27 September 2022

Date accepted : 29 September 2022

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000050, National Heart, Lung, and Blood Institute;

Award ID: R01HL135200

Custom metadata

ScienceOpen disciplines: Public health

Keywords: neighborhood,resilience,psychosocial factors,life’s simple 7,cardiovascular health

Data availability:

ScienceOpen disciplines: Public health

Keywords: neighborhood, resilience, psychosocial factors, life’s simple 7, cardiovascular health

Examining relationships between perceived neighborhood social cohesion and ideal cardiovascular health and whether psychosocial stressors modify observed relationships among JHS, MESA, and MASALA participants

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Abstract

Background

Methods

Results

Conclusion

Supplementary Information

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Global Health Next Generation Network

Most cited references 42

The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019

2021 ESC Guidelines on cardiovascular disease prevention in clinical practice

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