
==== Front
BMC Cardiovasc Disord
BMC Cardiovasc Disord
BMC Cardiovascular Disorders
1471-2261
BioMed Central London

39272001
4156
10.1186/s12872-024-04156-8
Research
A global analysis of the burden of ischemic heart disease attributable to diet low in fiber between 1990 and 2019
Wei Nana 1
Wang Lichao 2
Tang Bi 2
Huang Yuli 2
Xuan Ling 13855230121@163.com

2
1 Department of General Medicine, The first affiliated hospital of Bengbu Medical University, Bengbu, 233004 Anhui China
2 Department of Cardiovascular Medicine, The first affiliated hospital of Bengbu Medical University, Bengbu, China
14 9 2024
14 9 2024
2024
24 49121 5 2024
2 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.
Aim

Ischemic heart disease (IHD) represents a major cardiovascular condition heavily influenced by dietary factors. This study endeavors to assess the global, regional, and temporal impact of low-fiber diets on the burden of IHD.

Method

Leveraging data from the Global Burden of Disease (GBD) 2019 study, we analyzed the worldwide burden of IHD resulting from diet low in fiber using indices including death and disability-adjusted life years (DALY). This burden was further segmented based on variables including regions and countries. To track the evolution from 1990 to 2019, we utilized the Joinpoint regression model to estimate the temporal trend of IHD burden stemming from low-fiber diets.

Results

In 2019, a total of 348.85 thousand (95%UI: 147.57, 568.31) deaths and 7942.96 thousand (95%UI: 3373.58,12978.29) DALY (95% UI: 707.88, 1818) of IHD were attributed to diet low in fiber globally. These figures correspond to 3.82% of all IHD deaths and 4.36% of total IHD DALYs. The age-standardized death and DALY rates per 100,000 individuals were 4.48 (95% UI: 1.90,7.27) and 97.4(95%UI: 41.44, 158.88) respectively. However, significant regional disparities emerged in these age-standardized rates, with South Asia and Central Asia experiencing the highest rates. Between 1990 and 2019, we observed that most regions displayed a downward trend of the age-standardized DALY and death rate of IHD resulting from low-fiber diets, except for Central Sub-Saharan Africa and Southern Sub-Saharan Africa.

Conclusion

Our analysis underscores the substantial toll of IHD associated with low-fiber diets, particularly considering the significant regional variations. Therefore, it is imperative to sustain efforts to implement effective measures aimed at enhancing fiber intake worldwide, particularly in countries with lower socio-demographic indices.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-024-04156-8.

Keywords

IHD
Diet low in fiber
GBD 2019
Temporal trend
Science and Technology projects of Bengbu Medical College 20202020byzd168 Humanity and Social Science Research Project of Anhui Educational CommitteeSK2021A0433 issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcIntroduction

Ischemic heart disease (IHD) stands as a prevalent cardiovascular condition that poses a significant threat to global public health. According to recent statistics, in 2019, the number of individuals afflicted with IHD reached 197 million, representing 16.17% of all deaths and accounting for 7.19% of disability-adjusted life-years (DALY) globally [1]. Given these figures, primary prevention becomes paramount in mitigating or eliminating risk factors that influencing IHD.

Emerging studies showed that dietary compounds can significantly impact cardiovascular diseases in diverse manners [2]. Notably, dietary fiber, considered the seventh crucial nutrient for the body, is a vital and health-promoting component of our diet. It is widely acknowledged that sufficient dietary fiber intake aids in inhibiting the development and progression of cardiovascular diseases [3]. Further evidence has highlighted the impact of dietary fiber in reducing the occurrence and development of IHD [4–6]. For instance, a prospective study spanning 12.6 years and involving 490,311 subjects across 10 European countries revealed that an increment of 10 g of dietary fiber intakes per day correlated with 9% decrement in the risk of IHD [6]. Mechanistically, dietary fiber contributes to reducing IHD risk by lowering serum cholesterol levels, blood pressure, as well as levels of inflammatory and oxidative stress markers, critical factors in the progression of IHD [7, 8]. It has also demonstrated that dietary fiber enhances gut microbiota diversity, which is linked to the onset of cardiovascular diseases [9]. Nevertheless, it is noteworthy that most individuals fail to meet the recommended daily fiber intake worldwide.

However, so far, no studies have quantified the global burden of IHD associated with a low-fiber diet. Moreover, existing research exhibits variations in observation durations, analytical methodologies, and model specifications, posing challenges in comparing their findings. Fortunately, the GBD study provides a platform to assess the diet low in fiber associated IHD burden globally, utilizing standardized techniques [10, 11]. In particular, the burden of IHD is more severe among the elderly population [12, 13]. In the context of global aging, analyzing modifiable dietary risk factors for IHD is of great significance for policy formulation and disease prevention.

In summary, this study employed the GBD 2019 database to fulfill three primary goals: firstly, to quantify the worldwide impact of IHD stemming from a diet deficient in fiber, and categorize this impact based on variables including GBD regions and countries; secondly, to examine the trends in IHD burden associated with low-fiber diets from 1990 to 2019. The insights gained from this research could aid policymakers in pinpointing critical areas and crafting effective public health policies.

Methods

Overview

In 2020, the GBD Study conducted a thorough scientific evaluation of the diverse diseases, and risk factors worldwide, spanning 204 countries and territories from 1990 to 2019 [10, 11]. The global survey encompassed the whole world into 21 regions and further grouped into seven super regions. Moreover, the study stratified the nations into five developmental tiers, using a socio-demographic index (SDI). Our retrieval of data from the Institute for Health Metrics and Evaluation encompassed the number of DALYs (Disability-Adjusted Life Years) and deaths attributed to IHD caused by a low-fiber diet, globally, across geographical regions, SDI regions, and specific countries between 1990 and 2019, along with their age-standardized rates.

Estimation process

The primary source of dietary fiber data utilized by GBD 2019 is derived from nutrition surveys such as 24-hour diet recall. Furthermore, GBD 2019 study characterized a low-fiber diet as consuming less than 21–22 g of fiber daily on average, encompassing various sources such as fruits and grains [10, 11]. IHD was defined as I20 to I25. Elsewhere [10, 11], the GBD methods for estimating the disease burden attributed to specific factors were outlined. In brief, based on a large number of literature reviews and meta-analysis studies, GBD 2019 estimated the relative risk (RR) of IHD caused by a low-fiber diet and used the population attributable fraction (PAF) to estimate its degree of harm to the population. The average exposure level of the risk factor was assessed utilizing a Bayesian meta-regression framework and a spatiotemporal Gaussian process regression model. By multiplying the PAF by the number of IHD death and DALY, the number of IHD death and DALY caused by a low-fiber diet were obtained. The standardization of rates was calculated based on the World Standard Population published by the World Health Organization.

Statistical analysis

We presented comprehensive data accompanied by 95% uncertainty intervals (UI) concerning the IHD death and DALY, resulting from diets deficient in fiber globally, as well as categorized based on age, gender, geographical regions, and nations. Furthermore, the research utilized a Spearman correlation analysis to investigate the link between the SDI and the age-standardized IHD mortality and DALY rates, which are attributable to diets lacking in fiber. To analyze the temporal trends of the low-fiber diets associated IHD burden from 1990 to 2019, a Joinpoint regression model was utilized [14]. The research then determined the average annual percent change (AAPC) and its associated 95% confidence intervals [14]. These trends were subsequently classified as increasing (AAPC greater than 0), decreasing (AAPC less than 0), or remaining stable (where the 95% confidence interval encompassed 0). The Joinpoint Regression Program and R software used to perform data analyses. Statistical significance was defined as a P-value less than 0.05.

Results

Global burden of IHD attributable to diet low in fiber in 2019

In 2019, 7942.96 thousand (95%UI: 3373.58,12978.29) DALYs and 348.85 thousand (95%UI: 147.57, 568.31) deaths of IHD were related with diet low in fiber globally, accounting for 4.36% (95%UI: 1.81%,7.02%) DALY and 3.82% (95%UI: 1.58%,6.15%) death of total IHD, respectively (Table 1). In terms of age-standardized rate, the DALY rate changed from 176.79(95%UI: 76.41, 278.30, per 100,000 population) in 1990 to 97.4(95%UI:41.44,158.88, per 100,000 population) in 2019, with AAPC of -2.02% (95%CI: -2.06%, -1.98%). Also, the death rate significantly decreased (AAPC: -2.26%,95%CI: -2.29%, -2.22%), reaching 4.48(95%UI: 1.90, 7.27) in 2019 (Fig. 1).

Fig. 1 Temporal trend in IHD burden attributable to diet low in fiber in different regions from 1990 to 2019(red line indicated age-standardized death rate (per 100000 people), while blue line meant the age-standardized DALY rate (per 100000 people))

Table 1 Numbers and age-standardized rates of IHD death and DALY attributable to diet low in fiber in different regions in 2019. DALY, disability-adjusted life year; SDI, Socio-demographic index

	DALY	Death	
	Number(thousand)	Age-standardized rate

(per 100000 population)

	Number(thousand)	Age-standardized rate

(per 100000 population)

	
Global	7942.96(3373.58,12978.29)	97.4(41.44,158.88)	348.85(147.57,568.31)	4.48(1.90,7.27)	
SDI					
Low SDI	751.60(314.43,1217.66)	126.62(52.89,207.67)	25.97(10.87,42.64)	5.49(2.35,9.00)	
Low-middle SDI	2398.48(1076.66,3861.38)	165.40(74.95,266.36)	88.9(40.15,141.84)	7.11(3.23,11.37)	
Middle SDI	2434.99(1050.98,3938.48)	97.52(42.27,157.53)	98.91(43.04,162.31)	4.57(2.01,7.49)	
High-middle SDI	1386.99(511.90,2472.14)	70.70(26.18,126.22)	71.87(27.09,127.12)	3.69(1.39,6.50)	
High SDI	966.29(371.48,1604.17)	53.58(20.43,89.00)	63.01(24.85,102.55)	2.93(1.16,4.78)	
High income	1022.89(390.33,1696.95)	51.15(19.48,85.21)	67.87(26.45,111.05)	2.79(1.09,4.55)	
Australasia	22.44(8.72,37.19)	47.56(18.66,78.59)	1.41(0.55,2.36)	2.58(1.02,4.31)	
Western Europe	394.12(144.30,660.11)	44.37(16.20,74.88)	27.83(10.42,46.24)	2.58(0.95,4.29)	
High-income Asia Pacific	126.48(54.44,199.78)	31.58(13.79,50.20)	8.72(3.67,14.23)	1.61(0.70,2.58)	
High-income North America	413.92(159.15,694.25)	69.20(26.14,115.95)	26.36(10.42,43.52)	3.81(1.49,6.29)	
Southern Latin America	65.93(25.75,109.43)	80.85(31.67,133.80)	3.54(1.35,5.84)	4.19(1.60,6.92)	
Central Europe, eastern Europe, and central Asia	901.05(328.84,1598.80)	150.50(55.06,265.22)	48.8(18.17,85.37)	7.92(2.93,13.82)	
Central Asia	170.70(61.41,299.06)	240.37(87.15,419.51)	7.41(2.67,13.02)	13.15(4.74,22.81)	
Central Europe	178.69(66.72,318.27)	87.09(32.34,154.5)	11.32(4.35,19.85)	5.17(1.98,9.09)	
Eastern Europe	551.66(197.32,980.43)	168.78(59.96,299.72)	30.06(10.75,53.65)	8.77(3.12,15.66)	
Latin America and Caribbean	390.77(153.34,660.68)	65.67(25.68,111.03)	17.35(6.78,29.41)	3.05(1.19,5.17)	
Central Latin America	129.11(49.25,227.15)	54.10(20.62,95.23)	6.23(2.4,11)	2.74(1.06,4.84)	
Caribbean	51.19(19.01,91.75)	99.82(37.17,178.74)	2.27(0.86,3.99)	4.38(1.64,7.69)	
Tropical Latin America	172.97(65.67,295.39)	70.13(26.46,119.56)	7.08(2.66,11.84)	3.00(1.13,5.02)	
Andean Latin America	37.5(15.80,61.76)	65.42(27.55,108.03)	1.77(0.75,2.94)	3.27(1.37,5.43)	
North Africa and Middle East	433.94(173.70,751.92)	90.28(36.47,156.32)	16.49(6.71,28.6)	4.22(1.73,7.33)	
South Asia	2645.65(1153.86,4363.78)	175.93(76.41,289.75)	95.23(42.04,155.49)	7.45(3.35,12.22)	
Southeast Asia, East Asia, and Oceania	2369.43(1035.44,3773.10)	90.59(40.18,144.40)	96.35(42.89,153.46)	4.17(1.86,6.72)	
East Asia	891.15(321.01,1647.54)	46.68(16.81,85.80)	39.65(14.26,75.04)	2.35(0.85,4.35)	
Southeast Asia	1476.22(711.89,2253.37)	231.53(111.36,351.70)	56.63(27.43,86.02)	10.43(5.12,15.69)	
Oceania	2.05(0.94,3.94)	24.41(11.70,45.41)	0.07(0.03,0.12)	1.07(0.52,1.95)	
Sub-Saharan Africa	179.24(71.42,311.59)	35.61(14.27,61.66)	6.76(2.72,11.68)	1.75(0.69,3.02)	
Southern Sub-Saharan Africa	21.91(7.69,40.28)	37.27(13.28,67.87)	0.89(0.33,1.63)	1.83(0.68,3.37)	
Eastern Sub-Saharan Africa	65.60(28.28,112.46)	34.93(14.99,59.79)	2.29(0.98,3.93)	1.60(0.68,2.70)	
Central Sub-Saharan Africa	53.18(16.84,96.52)	92.36(29.71,167.04)	1.95(0.63,3.52)	4.53(1.52,8.15)	
Western Sub-Saharan Africa	38.55(17.55,67.1)	20.20(9.41,34.86)	1.63(0.76,2.80)	1.12(0.52,1.92)	

The age-standardized DALY and death rates of IHD due to diet low in fiber were 128.43(95%UI: 54.67,209.83) and 5.56(95%UI: 2.36,9.18) in males, while were 67.91(95% UI: 28.70,111.52) and 3.35(95%UI:1.47,5.86) in females. Meanwhile, the age-specific DALY and death rates of diet low in fiber-related IHD increased with aging in both genders (Fig.S1). The number of DALY of IHD resulting from diet low in fiber was highest in age groups of 50–54 in males, while in age groups of ≥ 80 years in females. While, the number of deaths of IHD associated with diet low in fiber was highest in age groups of ≥ 80 years in both genders.

The burden of IHD attributable to diet low in fiber by regions

The results were shown in Table 1. Among the 21 regions, the number (thousand) of diet low in fiber-related IHD DALYs ranged from 2.05(95%UI:0.94,3.94) in Oceania to 2645.65 (95%UI:1153.86,4363.78) in South Asia. While, Central Asia (240.37, 95% UI:87.15,419.51) has the largest age-standardized DALY rate of IHD associated with diet low in fiber, followed by Southeast Asia (231.53,95% UI: 111.36, 351.70), South Asia (175.93,95%UI:76.41,289.75) Eastern Europe (168.78, 95%UI: 59.96, 299.72). Western Sub-Saharan Africa (20.20, 95% UI: 9.41,34.86) has the lowest age-standardized DALY rate of IHD associated with diet low in fiber (Fig. 1). Similarly, the highest age-standardized death rate of IHD associated with diet low in fiber was also observed in Central Asia (13.15,95% UI: 4.74,22.81), and the lowest was observed in Oceania (1.07,95% UI: 0.52,1.95). The number (thousand) of diet low in fiber-related IHD deaths ranged from 0.07(95%UI:0.03,0.12) in Oceania to 95.23 (95%UI: 42.04, 155.49) in South Asia.

Between 1990 and 2019, most regions displayed a downward trend of the age-standardized DALY and death rate of IHD associated with diet low in fiber, except for Central Sub-Saharan Africa and Southern Sub-Saharan Africa (Fig. 1). In Central Sub-Saharan Africa, both of the DALY and death rates of diet low in fiber-related IHD significantly increased, with AAPC of 0.93% (95%CI: 0.88%,0.98%) and 1.09% (95%CI: 1.04%,1.14%). Likewise, in Southern Sub-Saharan Africa, the death rate of IHD resulting from diet low in fiber also significantly increased (AAPC: 0.24%,95%CI: 0.11%, 0.39%), while the DALY rate remained stable (AAPC: -0.03%,95%CI: -0.15%, 0.09%). Among the countries which had a downward trend of the age-standardized DALY and death rate of IHD resulting from diet low in fiber, the largest and smallest decrease was observed in Australasia (AAPC: -4.79%,95%CI: -4.83%, -4.74% and − 4.67%,95%CI: -4.73%, -4.62%) and Eastern Europe (AAPC: -0.32%, 95%CI: -0.48%, -0.14% and − 0.51%,95%CI: -0.72%, -0.26%), respectively.

The burden of IHD attributable to diet low in fiber by countries and territories

The number (thousand) of IHD DALYs (1627.40,95%UI: 598.48, 2895.89) and deaths (59.30,95%UI:22.07,105.77) resulting from diet low in fiber was largest in India, followed by China, United States of America, and Indonesia (Table S1). As for the age-standardized DALY rate of IHD resulting from diet low in fiber, Mongolia tops the first with 613.76(95%UI: 303.14, 958.17) DALYs, followed by Afghanistan, Tajikistan, Yemen and Uzbekistan. Mongolia also has the largest age-standardized death rate of IHD attributable to diet low in fiber (Fig. 2). Table S1 listed the results of the temporal trend of IHD resulting from diet low in fiber for each country between 1990 and 2019. A notable increase in the age-standardized DALY rate is evident in 30 countries and territories, including Burundi, Iraq, the Philippines, and Ukraine, among others. While, Cuba has the largest decrease of IHD attributable to diet low in fiber, with AAPC of -9.53% (95%CI: -9.66%, -9.39%) for DALY rate and − 8.26% (95%CI: -8.43%, -8.08%) for death rate (Table S1).

Fig. 2 The IHD burden attributable to diet low in fiber in different countries and territories in 2019

The burden of IHD attributable to diet low in fiber in regions with different SDI

In 2019, The age-standardized DALY and death rates (per 100,000 population) of IHD resulting from were highest in Low-middle SDI region (165.40,95%UI: 74.95,266.36 and 7.11,95%UI: 3.23,11.37), while the minimum estimates were in high SDI region (53.58, 95%UI: 20.43,89.00 and 2.93, 95% UI: 1.16,4.78) (Table 1). There were none significant correlations between SDI and DALY (r=-0.01, P = 0.833) and death (r=-0.06, P = 0.375) rates of IHD resulting from diet low in fiber burden (Fig S2). Between 1990 and 2019, all the five SDI regions showing a downward trend of burden of IHD resulting from diet low in fiber, however, from High SDI to low SDI, the degree of decline progressive reduction (Fig. 1).

Discussion

This study offers a comprehensive evaluation of the global impact of IHD stemming from a diet deficient in fiber. As per our knowledge, this marks the inaugural research to delve into this matter, yielding several noteworthy insights that demand the attention of health policymakers. This study underscores a substantial global burden of IHD resulting from a fiber-deficient diet, affecting a significant populace. Specifically, in 2019, diet deficient in fiber accounted for a notable share of IHD-related fatalities (3.82%) and DALY (4.36%), exhibiting significant geographical disparities. Furthermore, we discerned a concerning upward trajectory in the number of IHD-related deaths and DALY attributed to a fiber-deficient diet globally. These disclosures possess profound implications for policymakers, especially in the global pursuit to address the obstacles stemming from IHD.

Globally, dietary fiber consumption remains insufficient. Numerous nations recommend 25–35 g of dietary fiber daily for adults. Yet, in the United States from 2011 to 2012, men averaged 20.5 g daily, while women consumed 16.2 g. Similarly, in Canada in 2011, men averaged 16.5 g, and women 14.3 g. In the United Kingdom, from 2009 to 2012, men consumed an average of 14.7 g, while women averaged 12.8 g [15]. In Asia, Japanese individuals consumed between 15 and 20 g daily in the 1980s and 1990s [16]. In comparison, China had a relatively higher intake in 2011, with 19.4 g for men and 17.6 g for women [17]. Therefore, to address this IHD burden stemming from low-fiber diets, it is highly necessary to comprehensively analyze the global distribution of the burden of IHD associated with insufficient dietary fiber intake.

Our research indicates that the diet low in fiber associated IHD burden is more significant among males and individuals of advanced age. This disparity may stem from the tendency of males and younger adults towards consuming less nutritious dietary choices [18], as well as the delayed impact of dietary intake on health outcomes, ultimately leading to an elevated risk of developing IHD [19]. Additionally, there is often a lack of comprehension among males and older individuals regarding the interconnection between dietary intake and overall health [20]. Also, the burden for females were lower, potentially stemming from a strong correlation with estrogen levels prior to menopause, as estrogens are known to exhibit antioxidant and antiapoptotic effects on cardiomyocytes during ischemic conditions [21]. Consequently, to alleviate the burden of IHD, it’s crucial to prioritize early nutritional interventions (such as health education) targeting young males and adopt effective plans for older males.

Across regions, geographical disparities played a significant role in shaping the epidemiological patterns of IHD resulting from a diet low in fiber. Our analysis revealed that regions like South Asia, Central Asia, Southeast Asia (including countries e.g., Mongolia, Afghanistan, Tajikistan, Uzbekistan and Yemen) have exhibited higher rates of IHD resulting from dietary in low fiber. The primary cause of this disparity lies in socioeconomic disparities and the uneven spread of dietary factors among diverse regions. This can be evidenced by our findings that high SDI region has the minimum burden estimates. Those residing in high-SDI areas often exhibit healthier dietary patterns, preferring to consume foods that are nutritionally beneficial like whole grains and fruits, in comparison to those residing in lower-SDI regions [22–24]. A study in China also found that dietary fiber intake increased among people in highly urbanized communities, while the opposite trend was observed in low-urbanization areas [17], suggesting that socioeconomic imbalances and uneven distribution may influence dietary habits. Furthermore, data gathered from 52 nations revealed that urban areas experiencing an upsurge in income levels consume greater quantities of fruits and vegetables [25]. Besides, individuals residing in low- and middle-income regions might be unaware of the positive health impacts of fiber intake, coupled with their constrained access to fresh food markets stemming from transportation limitations [26, 27]. Additionally, numerous low-SDI countries prioritize exporting fruits and vegetables rich in dietary fiber instead of consuming them locally, contributing significantly to an increased risk of exposure to a low-fiber diet [28]. Furthermore, additional research is crucial to identify the underlying factors that contribute to the region-level heterogeneity in the IHD burden resulting from diet in low fibers.

Between 1990 and 2019, we observed that most regions displayed a downward trend of the burden of IHD attributable to diet low in fiber, except for Central Sub-Saharan Africa and Southern Sub-Saharan Africa. In sub-Saharan Africa, food prices tend to be relatively high, while dietary quality lags behind [29]. Moreover, in specific nations and their neighboring regions, both domestic and international tensions persist, which have significantly hampered food production and trade, thus contributing to poor dietary quality [30]. It’s noteworthy that the global consumption of dietary fiber is currently suboptimal. To alleviate the disease burden resulting from low-fiber diet in various regions, comprehensive interventions are imperative, particularly in low-SDI regions. For instance,

utilizing mass media, educational initiatives and the adoption of favorable food pricing policies can effectively promote dietary fiber consumption by enhancing public knowledge of healthy dietary practices [31, 32]. It is imperative to devise public health strategies tailored to the dietary patterns and disease burdens in diverse regions.

The interpretation of our research is subject to certain constraints. Firstly, our estimations heavily relied on the availability of data. Although nationwide censuses and surveys furnish valuable data on IHD mortality, the scope and reliability of such information is still constrained, particularly in remote and economically deprived areas, thereby posing challenges to the precision of burden assessments. Secondly, when assessing the magnitude of the effect of the correlation between a fiber-deficient diet and IHD in the GBD 2019 study, it might be subject to potential confounding factors, and interactions among dietary components. As a global epidemiological analysis, such as missing data, inconsistency, and large methodological variation between data sources in different countries may also introduce bias to the results. Thirdly, for countries with large territorial areas, such as China and the United States, we have not fully analyzed the burden of IHD related to insufficient dietary fiber within their regions. A more refined analysis of disease burden at a geographical scale could help formulate better public health policies.

Conclusions

Our research underscores the pressing global concern of significantly rising cases of IHD attributed to diet in low fiber, highlighting the urgent need for health policymakers to take swift action and intervene. Moreover, our research highlights specific regions burdened with heavy disease rates, alongside vulnerable groups that necessitate increased attention and appropriate resources. Fundamentally, our discoveries provide crucial perspectives that can contribute towards formulating public health policies designed to alleviate and adapt to the health implications of a low-fiber diet.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Acknowledgements

We highly appreciate the work by the GBD 2019 collaborators.

Author contributions

Conceptualization, N.W. and L.X.; methodology, N.W.; software, N.W.; validation, L.X. and L.W.; formal analysis, N.W.; investigation, N.W.; resources, N.W.; data curation, L.W.; writ-ing—original draft preparation, N.W.; writing—review and editing, L.W.; visualization, N.W.; supervision, B.T., Y.H. and L.X.; project administration, L.X.; funding acquisition, L.X. and B.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by grants from the Humanities and Social Science Project of Anhui Provincial Education Department (SK2021A0433) and Science and Technology projects of Bengbu Medical College 2020 (2020byzd168).

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Humanity and Social Science Research Project of Anhui Educational Committee(SK2021A0433). Science and Technology projects of Bengbu Medical College 2020 (2020byzd168).

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References

1. Safiri S Karamzad N Singh K Burden of ischemic heart disease and its attributable risk factors in 204 countries and territories, 1990–2019 Eur J Prev Cardiol 2022 29 2 420 31 10.1093/eurjpc/zwab213 34922374
Safiri S, Karamzad N, Singh K. Burden of ischemic heart disease and its attributable risk factors in 204 countries and territories, 1990–2019. Eur J Prev Cardiol. 2022;29(2):420–31.34922374 10.1093/eurjpc/zwab213
2. Nestel PJ Mori TA Dietary patterns, dietary nutrients and cardiovascular disease Rev Cardiovasc Med 2022 23 1 17 10.31083/j.rcm2301017 35092209
Nestel PJ, Mori TA. Dietary patterns, dietary nutrients and cardiovascular disease. Rev Cardiovasc Med. 2022;23(1):17.35092209 10.31083/j.rcm2301017
3. Soliman GA Dietary Fiber, atherosclerosis, and Cardiovascular Disease Nutrients 2019 11 5 1155 10.3390/nu11051155 31126110
Soliman GA. Dietary Fiber, atherosclerosis, and Cardiovascular Disease. Nutrients. 2019;11(5):1155.31126110 10.3390/nu11051155
4. Threapleton DE Greenwood DC Evans CE Dietary fiber intake and risk of cardiovascular disease: systematic review and meta-analysis BMJ 2013 347 f6879 10.1136/bmj.f6879 24355537
Threapleton DE, Greenwood DC, Evans CE, et al. Dietary fiber intake and risk of cardiovascular disease: systematic review and meta-analysis. BMJ. 2013;347:f6879.24355537 10.1136/bmj.f6879
5. Crowe FL Key TJ Appleby PN Dietary fbre intake and ischaemic heart disease mortality: the European prospective investigation into Cancer and Nutrition-Heart study Eur J Clin Nutr 2012 66 8 950 6 10.1038/ejcn.2012.51 22617277
Crowe FL, Key TJ, Appleby PN. Dietary fbre intake and ischaemic heart disease mortality: the European prospective investigation into Cancer and Nutrition-Heart study. Eur J Clin Nutr. 2012;66(8):950–6.22617277 10.1038/ejcn.2012.51
6. Perez-Cornago A Crowe FL Appleby PN Plant foods, dietary fibre and risk of ischaemic heart disease in the European prospective investigation into Cancer and Nutrition (EPIC) cohort Int J Epidemiol 2021 50 1 212 22 10.1093/ije/dyaa155 33245137
Perez-Cornago A, Crowe FL, Appleby PN, et al. Plant foods, dietary fibre and risk of ischaemic heart disease in the European prospective investigation into Cancer and Nutrition (EPIC) cohort. Int J Epidemiol. 2021;50(1):212–22.33245137 10.1093/ije/dyaa155
7. Jama HA, Snelson M, Schutte AE, Muir J, Marques FZ. Recommendations for the Use of Dietary Fiber to improve blood pressure control. Hypertension. 2024 Apr 8.
8. Hornero-Ramirez H Aubin A Michalski MC Multifunctional dietary interventions, low-grade inflammation and cardiometabolic profile: a scoping review Front Immunol 2024 15 1304686 10.3389/fimmu.2024.1304686 38476230
Hornero-Ramirez H, Aubin A, Michalski MC, et al. Multifunctional dietary interventions, low-grade inflammation and cardiometabolic profile: a scoping review. Front Immunol. 2024;15:1304686.38476230 10.3389/fimmu.2024.1304686
9. Strasser B Wolters M Weyh C The effects of Lifestyle and Diet on Gut Microbiota Composition, inflammation and muscle performance in our Aging Society Nutrients 2021 13 6 2045 10.3390/nu13062045 34203776
Strasser B, Wolters M, Weyh C, et al. The effects of Lifestyle and Diet on Gut Microbiota Composition, inflammation and muscle performance in our Aging Society. Nutrients. 2021;13(6):2045.34203776 10.3390/nu13062045
10. GBD 2019 Diseases and Injuries Collaborators Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of Disease Study 2019 Lancet 2020 396 10258 1204 22 10.1016/S0140-6736(20)30925-9 33069326
GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of Disease Study 2019. Lancet. 2020;396(10258):1204–22.33069326 10.1016/S0140-6736(20)30925-9
11. GBD 2019 Risk Factors Collaborators Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of Disease Study 2019 Lancet 2020 396 10258 1223 49 10.1016/S0140-6736(20)30752-2 33069327
GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of Disease Study 2019. Lancet. 2020;396(10258):1223–49.33069327 10.1016/S0140-6736(20)30752-2
12. Safiri S Asghari KM Sullman MJ The global burden of diseases and injuries among older adults Int J Aging 2023 1 e16 10.34172/ija.2023.e16
Safiri S, Asghari KM, Sullman MJ. The global burden of diseases and injuries among older adults. Int J Aging. 2023;1:e16.10.34172/ija.2023.e16
13. Mousavi SE Fazlollahi A Nejadghaderi SA The burden of ischemic heart disease among adults 70 years and older in Iran, 1990–2019 Int J Aging 2023 1 1 e9 9 10.34172/ija.2023.e9
Mousavi SE, Fazlollahi A, Nejadghaderi SA, et al. The burden of ischemic heart disease among adults 70 years and older in Iran, 1990–2019. Int J Aging. 2023;1(1):e9–9.10.34172/ija.2023.e9
14. Kim HJ Fay MP Feuer EJ Permutation tests for joinpoint regression with applications to cancer rates Stat Med 2000 19 335 51 10.1002/(SICI)1097-0258(20000215)19:3<335::AID-SIM336>3.0.CO;2-Z 10649300
Kim HJ, Fay MP, Feuer EJ, et al. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. 2000;19:335–51.10649300 10.1002/(SICI)1097-0258(20000215)19:3<335::AID-SIM336>3.0.CO;2-Z
15. Stephen AM Champ MM Cloran SJ Dietary fiber in Europe: current state of knowledge on defnitions, sources, recommendations, intakes and relationships to health Nutr Res Rev 2017 30 149 90 10.1017/S095442241700004X 28676135
Stephen AM, Champ MM, Cloran SJ, et al. Dietary fiber in Europe: current state of knowledge on defnitions, sources, recommendations, intakes and relationships to health. Nutr Res Rev. 2017;30:149–90.28676135 10.1017/S095442241700004X
16. Nakaji S Sugawara K Saito D Trends in dietary fber intake in Japan over the last century Eur J Nutr 2002 41 222 7 10.1007/s00394-002-0379-x 12395216
Nakaji S, Sugawara K, Saito D, et al. Trends in dietary fber intake in Japan over the last century. Eur J Nutr. 2002;41:222–7.12395216 10.1007/s00394-002-0379-x
17. Wang HJ Wang ZH Zhang JG Trends in dietary fber intake in Chinese aged 45 years and above, 1991–2011 Eur J Clin Nutr 2014 68 619 22 10.1038/ejcn.2014.24 24619105
Wang HJ, Wang ZH, Zhang JG, et al. Trends in dietary fber intake in Chinese aged 45 years and above, 1991–2011. Eur J Clin Nutr. 2014;68:619–22.24619105 10.1038/ejcn.2014.24
18. Imamura F Micha R Khatibzadeh S Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic assessment Lancet Glob Health 2015 3 e132 142 10.1016/S2214-109X(14)70381-X 25701991
Imamura F, Micha R, Khatibzadeh S, et al. Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic assessment. Lancet Glob Health. 2015;3:e132–142.25701991 10.1016/S2214-109X(14)70381-X
19. Evans CEL Dietary fibre and cardiovascular health: a review of current evidence and policy Proc Nutr Soc 2020 79 1 61 7 10.1017/S0029665119000673 31266545
Evans CEL. Dietary fibre and cardiovascular health: a review of current evidence and policy. Proc Nutr Soc. 2020;79(1):61–7.31266545 10.1017/S0029665119000673
20. Guine RP Duarte J Ferreira M Knowledge about sources of dietary fibres and health effects using a validated scale: a cross-country study Public Health 2016 141 100 12 10.1016/j.puhe.2016.08.015 27931984
Guine RP, Duarte J, Ferreira M, et al. Knowledge about sources of dietary fibres and health effects using a validated scale: a cross-country study. Public Health. 2016;141:100–12.27931984 10.1016/j.puhe.2016.08.015
21. Zengul AG Demark-Wahnefried W Barnes S Associations between Dietary Fiber, the fecal microbiota and Estrogen Metabolism in Postmenopausal women with breast Cancer Nutr Cancer 2021 73 7 1108 17 10.1080/01635581.2020.1784444 32590914
Zengul AG, Demark-Wahnefried W, Barnes S, et al. Associations between Dietary Fiber, the fecal microbiota and Estrogen Metabolism in Postmenopausal women with breast Cancer. Nutr Cancer. 2021;73(7):1108–17.32590914 10.1080/01635581.2020.1784444
22. Allen L Williams J Townsend N Socioeconomic status and non-communicable disease behavioral risk factors in low-income and lower-middle-income countries: a systematic review Lancet Glob Health 2017 5 e277 89 10.1016/S2214-109X(17)30058-X 28193397
Allen L, Williams J, Townsend N, et al. Socioeconomic status and non-communicable disease behavioral risk factors in low-income and lower-middle-income countries: a systematic review. Lancet Glob Health. 2017;5:e277–89.28193397 10.1016/S2214-109X(17)30058-X
23. Darmon N Drewnowski A Does social class predict diet quality? Am J Clin Nutr 2008 87 1107 17 10.1093/ajcn/87.5.1107 18469226
Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87:1107–17.18469226 10.1093/ajcn/87.5.1107
24. Giskes K Avendano M Brug J A systematic review of studies on socioeconomic inequalities in dietary intakes associated with weight gain and overweight/obesity conducted among European adults Obes Rev 2010 11 413 29 10.1111/j.1467-789X.2009.00658.x 19889178
Giskes K, Avendano M, Brug J, et al. A systematic review of studies on socioeconomic inequalities in dietary intakes associated with weight gain and overweight/obesity conducted among European adults. Obes Rev. 2010;11:413–29.19889178 10.1111/j.1467-789X.2009.00658.x
25. Hall JN Moore S Harper SB Global variability in fruit and vegetable consumption Am J Prev Med 2009 36 402 e409405 10.1016/j.amepre.2009.01.029 19362694
Hall JN, Moore S, Harper SB, et al. Global variability in fruit and vegetable consumption. Am J Prev Med. 2009;36:402–e409405.19362694 10.1016/j.amepre.2009.01.029
26. Salehi L, Eftekhar H, Mohammad K et al. Consumption of fruit and vegetables among elderly people: a cross sectional study from Iran. Nutr J 2010, 9, 2.
27. Ramirez-Silva I, Rivera JA, Ponce X et al. Fruit and vegetable intake in the Mexican population: results from the Mexican National Health and Nutrition Survey 2006. Salud Publica Mex.20099, 51 Suppl 4, S574–585.
28. Satheannoppakao W Aekplakorn W Pradipasen M Fruit and vegetable consumption and its recommended intake associated with sociodemographic factors: Thailand National Health Examination Survey III Public Health Nutr 2009 12 2192 8 10.1017/S1368980009005837 19454123
Satheannoppakao W, Aekplakorn W, Pradipasen M. Fruit and vegetable consumption and its recommended intake associated with sociodemographic factors: Thailand National Health Examination Survey III. Public Health Nutr. 2009;12:2192–8.19454123 10.1017/S1368980009005837
29. Lock K, Stuckler D, Charlesworth K, et al. Potential causes and health effects of rising global food prices. Volume 339. BMJ; 2009. p. b2403.
30. Friel S Jamieson L Political economy, trade relations and health inequalities: lessons from general health Community Dent Health 2019 36 2 152 6 31046206
Friel S, Jamieson L. Political economy, trade relations and health inequalities: lessons from general health. Community Dent Health. 2019;36(2):152–6.31046206
31. Zhang D Giabbanelli PJ Arah OA Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model Am J Public Health 2014 104 1217 22 10.2105/AJPH.2014.301934 24832414
Zhang D, Giabbanelli PJ, Arah OA, et al. Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model. Am J Public Health. 2014;104:1217–22.24832414 10.2105/AJPH.2014.301934
32. Afshin A Penalvo J Del Gobbo L CVD Prevention through Policy: a review of Mass Media, Food/Menu labeling, Taxation/Subsidies, Built Environment, School Procurement, Worksite Wellness, and Marketing standards to improve Diet Curr Cardiol Rep 2015 17 98 10.1007/s11886-015-0658-9 26370554
Afshin A, Penalvo J, Del Gobbo L, et al. CVD Prevention through Policy: a review of Mass Media, Food/Menu labeling, Taxation/Subsidies, Built Environment, School Procurement, Worksite Wellness, and Marketing standards to improve Diet. Curr Cardiol Rep. 2015;17:98.26370554 10.1007/s11886-015-0658-9
