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Abstract

Objective

We explored correlations between the Dietary Inflammatory Index (DII) and fracture risk in older adults.

Methods

We systematically searched MEDLINE, PubMed, Science Direct, Scopus, and CNKI for all relevant epidemiological studies published through October 16, 2023. Because observational studies were included in the meta-analysis, we used a random-effects model to pool the study-specific effect sizes and 95% confidence intervals (CIs). We assessed study quality using the Newcastle–Ottawa scale. This meta-analysis was registered in PROSPERO.

Results

Eight studies with 462,986 participants were included, with five cohort studies, two cross-sectional studies, and one case–control study. An analysis of heterogeneity among the eight included studies resulted in I² = 87.1%, indicating significant between-study heterogeneity; hence, the random-effects model was adopted to generate the combined effect size. We found that the DII was positively associated with fracture (relative risk: 1.188, 95% CI: 1.043–1.354). This result was further confirmed in leave-one-out sensitivity analysis.

Conclusions

Our study provides evidence suggesting that diets high in pro-inflammatory components might increase the fracture risk among older people. Decreased consumption of pro-inflammatory foods and increased consumption of anti-inflammatory foods are suggested to prevent adverse fracture outcomes. More prospective studies involving both sexes are warranted to verify the results.

Keywords

Dietary Inflammatory Index fracture risk older adult meta-analysis review chronic inflammation

Introduction

Older adults are particularly susceptible to fractures, which can lead to high rates of morbidity and mortality and place a heavy burden on health care systems worldwide.¹ Studies show that between 1990 and 1992, the incidence of hip fracture in people over 50 years old was 83/100,000 for men and 80/100,000 for women. Between 2002 and 2006, this incidence increased to 129/100,000 for men and 229/100,000 for women.² Fracture susceptibility is influenced by various factors, including diet, lifestyle, and age-related bone fragility. Multiple chronic diseases, such as osteoporosis and fractures, are closely linked to chronic inflammation, which plays a key role in tissue damage.^3,4 A large number of studies have suggested that diet, as a major source of biologically active compounds, may mediate the inflammatory response.^5,6 Recent research has increasingly focused on the role of dietary factors, particularly the inflammatory potential of the diet, in influencing the fracture risk among older people.⁷

A dietary measure developed according to the literature, the Dietary Inflammatory Index (DII), has been shown to be effective in assessing an individual’s diet-related propensity for overall inflammation.⁸ There appears to be a strong relationship between the DII and bio-humoral inflammatory parameters; previous research has shown that higher DII scores (indicating a more pro-inflammatory diet) are significantly associated with serum inflammatory indicators (such as C-reactive protein [CRP]).^9,10 A more pro-inflammatory diet, as indicated by a higher DII, may exacerbate systemic inflammation, which is associated with processes such as bone remodeling and turnover. A large number of recent studies have investigated the relationship between fractures and DII scores. In two studies, an increased DII score was positively correlated with fracture risk.^6,11 However, one multi-racial cohort study of 92,694 postmenopausal women exhibited an inverse association, indicating that women with high DII (more inflammatory) scores had a lower total fracture risk after multivariable adjustment.¹² Although early data suggest a strong association between the DII and fracture risk, there is ongoing debate about the relationship between the DII and bone disease owing to inconsistent results from different epidemiological studies. These discrepancies may be related to differences in age, sex, race and ethnicity, as well as observation period. To our knowledge, no comprehensive review or meta-analysis has been conducted to determine the association between fractures and the DII in the older adult population. A comprehensive review and meta-analysis of the literature is needed to determine whether there is an association between fracture and the DII in older adults.

The aim of the present analysis was to evaluate the association of the DII with fracture risk in the older adult population and provide theoretical support and guidance for the use of nutrition and diet to reduce the risk of fractures in this group.

Methods

This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.¹³ The study was registered in PROSPERO (CRD42023491860). The current study strictly followed a pre-set protocol. Ethical approval and informed consent were not required for this meta-analysis.

Search strategy

Relevant literature in the MEDLINE, PubMed, Science Direct, Scopus, CNKI databases, from database inception until 16 October 2023, were retrieved using the keywords “Dietary Inflammatory Index,” “fracture,” and “elderly,” as well as various combinations (e.g., “inflammatory diet index,” “pro-inflammatory diet,” “break,” “crack,” “older population,” “aged”).

Inclusion and exclusion criteria

The inclusion criteria for studies were as follows: data on the association between the DII and fracture were reported, publications in the English language, human studies with participants aged ≥60 years old, randomized controlled trials (RCTs), and cohort, case–control, or cross-sectional studies.

Exclusion criteria were duplicate studies, case reports, reviews, meta-analyses, animal studies, editorials, letters to the editor, and commentaries.

Literature screening and data extraction

The screening was carried out following the exclusion of duplicate articles. Two reviewers independently screened the studies according to title and abstract, followed by full-text screening. Any disagreements or inconsistencies were resolved in consultation with a third reviewer. The following data were extracted from the included studies: first author, year, country, study design, baseline characteristics of patients, sample size, and risk of fracture (hazard ratio [HR, relative risk [RR], odds ratio [OR]). The multivariable-adjusted ORs or HR and their corresponding 95% confidence intervals (CIs) were extracted, prioritizing effect sizes adjusted for the maximum number of confounders in multivariable models. The RR was calculated from the original data if not provided directly.

Quality assessment

Study quality was assessed using the Newcastle–Ottawa scale (NOS), and studies with NOS scores ≥7 were considered high quality.¹⁴

Data synthesis

Pooled RRs were calculated with their corresponding 95% CIs to determine whether the highest category of DII scores was a risk factor for fracture in older people. Adjusted ORs and HRs were considered equivalent estimators of RRs.¹⁵ Studies were considered as having non-significant heterogeneity with an I² index of 0% to 30%, moderate heterogeneity with 30% to 50%, substantial heterogeneity with 50% to 90%, and considerable heterogeneity with I² more than 90%.¹⁶ Furthermore, we used tau-squared (T²) to measure the variance in the true effect as an estimate of absolute heterogeneity in effect sizes.¹⁷ The fixed-effects model was used in cases of no detected heterogeneity, and the random-effects model was used if there was significant heterogeneity among the included studies.¹⁵ Because multiple observational study designs were included in this meta-analysis, only the random-effects model was a suitable choice.¹⁷ Subgroup analyses were conducted to identify potential sources contributing to the observed high heterogeneity. In this meta-analysis, P < 0.05 was considered to indicate statistically significant differences between groups. The Cochrane Collaboration’s Review Manager software (RevMan version 5.4) and Stata version 15.1 (StataCorp LLC, College Station, TX, USA) were used to perform the meta-analysis.

Results

Literature search

A complete search of PubMed and EMBASE yielded a total of 155 publications. After the elimination of duplicates, the count was reduced to 87 publications. Following the initial screening of titles and abstracts, 87 papers remained for full-text evaluation, excluding 68 articles deemed irrelevant to the scope of our investigation. After the full-text review, 11 studies were excluded; thus, eight studies met the criteria for inclusion in this meta-analysis, as shown in the PRISMA flow chart (Figure 1).

Figure 1.

PRISMA flow diagram for this systematic review and meta-analysis. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Characteristics

Eight articles with a total of 462,986 participants were included, of which five were cohort studies, two were cross-sectional, and one was a case-control study. Regarding study location, four studies were conducted in the United States, two in China, one in Australia, and one in Brazil. Most studies included men and women, with one study¹² enrolling only women. The basic characteristics of the included studies are shown in Table 1.

Table 1.

Characteristics of each cohort from eligible studies.

First author	Year	Country	Study design	Age (mean ± SD)	Sex (% women)	Sample size	Fracture site	Risk	Adjustment
Cervo⁷	2019	Australia	Cohort	63.0 ± 7.5	0%	536	Any	1.090 (1.01–1.175)	Age, body mass index, and baseline total hip bone mineral density
Cervo⁷	2019	Australia	Cohort	63.0 ± 7.5	100%	562	Any	0.878 (0.80–0.964)
Fung³³	2015	USA	Cohort	60	100%	74,540	Any	1.14 (0.96– 1.36)	Age, energy intake, BMI, smoking, physical activity, postmenopausal hormone use (women), thiazides, furosemide, anti-inflammatory steroids, calcium supplements, multivitamin supplements
Fung³³	2015	USA	Cohort	60	0%	38,305	Any	0.86 (0.64– 1.16)
Mazidi⁶	2017	USA	Cross-sectional	68.05	48.70%	18,318	Hip fracture	1.35 (0.92–1.99)	Calcium intake; trend in BMD across DII quarters remained significant for total femur, femoral neck, trochanter, and intertrochanter BMD
				68.05	48.70%	18,318	Wrist fracture	1.37 (1.18–1.59)
				68.05	48.70%	18,318	Spine fracture	1.24 (0.94–1.64)
Morimoto³⁴	2019	Brazil	Cross-sectional	69.7 ± 13.5	0%	684	Any	1.62 (0.86–3.05)	Diabetes mellitus and osteoporosis
Morimoto³⁴	2019	Brazil	Cross-sectional	69.7 ± 13.5	100%	1585	Any	0.88 (0.61–1.27)	Diabetes mellitus and osteoporosis
Orchard¹²	2017	USA	Cohort	63	100%	92,694	Lower arm fracture	0.86 (0.81–0.91)	Age, race and ethnicity, DII (baseline), CT, parental history of fracture, personal history of fracture at age 55 years or older, smoking, physical activity, region, diabetes, female hormone use, NSAID use, total calcium intake. randomization arm in CaD trial, corticosteroid use (screening), inflammatory bowel disease, rheumatoid arthritis, weight, and height
				63	100%	92,694	Hip fracture	0.92 (0.84–1.01)
				63	100%	92,694	Any	0.89 (0.87–0.92)
Su³⁵	2022	China	Cohort	72.39 ± 5.01	0%	3995	Any	1.56 (1.14–2.14)	Age, BMI, current smoking, previous fracture, hypertension, diabetes, chronic obstructive lung disease, cardiovascular disease, rheumatoid arthritis, nonsteroidal anti-inflammatory agent use, osteoporosis medication, vitamin D status, physical activity level
Su³⁵	2022	China	Cohort	72.59 ± 5.36	100%	3995	Any	1.00 (0.77–1.30)
Veronese⁹	2019	USA	Cohort	60.6 ± 9.1	0%	1577	Any	0.91 (0.54–1.54)	BMI, education level, personal income, smoking status, time spent on physical activity, family history of fracture, calcium supplements, multivitamin use
Veronese⁹	2019	USA	Cohort	60.6 ± 9.1	100%	2071	Any	1.46 (1.02–2.11)
Zhang¹¹	2017	China	Case-control	67.5	74.40%	2100	Hip fracture	2.44 (1.73–3.45)	Age, total energy intake, race and ethnicity, body mass index, education, smoking habits, yearly income, Charlson co-morbidity index, use of drugs positively affecting bone metabolism, Physical Activity Scale for the Elderly

DII, Dietary Inflammatory Index; BMI, body mass index; BMD, bone mineral density; CT, computed tomography, NSAID, non-steroidal anti-inflammatory drug; CaD, calcium plus vitamin D supplement.

Association of the DII and fracture risk in older adults

The relationship between the DII and fracture risk in older adults was reported in eight studies. An analysis of heterogeneity among the eight included studies resulted in I² = 87.1% and T² = 0.0213, indicating significant between-study heterogeneity; hence, the random-effects model was adopted to generate the combined effect size. The pooled results showed that overall, patients who consumed an anti-inflammatory diet reported significantly fewer fractures than patients in the control groups. We obtained an RR = 1.086 (95% CI: 1.24–1.92, P = 0.072), indicating that a pro-inflammatory diet (high DII scores) increased the risk of fracture in older people by 8.6% (Figure 2). Because there were only eight publications included in this study, sensitivity analysis was used to determine the source of heterogeneity. As shown in the sensitivity analysis forest map in Figure 3, after excluding Orchard’s¹² study, the heterogeneity of the results was significantly reduced (I² = 80.4% and T² = 0.0399), with the pooled result of the remaining studies maintaining significance (RR: 1.188, 95% CI: 1.043–1.354, P = 0.010). To identify the potential influence of a single study on the pooled results, each single study was excluded in turn, and the results of the remaining included studies were pooled. The pooled RR did not change significantly (Figure 3).

Figure 2.

Forest plot of the Dietary Inflammatory Index and fracture risk for all included studies. RR, relative risk; CI, confidence interval.

Figure 3.

Sensitivity analysis of the Dietary Inflammatory Index and fracture risk for all included studies. CI, confidence interval.

Subgroup analysis

To explore the source of heterogeneity, we conducted subgroup analysis (Table 2). The pooled results of five cross-sectional studies showed that the DII had a positive effect on fracture risk (RR = 1.266, 95% CI: 1.083–1.480). However, a negative relationship with fracture risk was observed in the results of 11 cohort studies (RR = 0.979, 95% CI: 0.906–1.057). The results showed that the high heterogeneity was mainly owing to sex as well as study design and type.

Table 2.

Subgroup analysis of Dietary Inflammatory Index for fracture risk.

Subgroup	Number of studies	Heterogeneity (I²)	Variance (T²)	P	Relative risk (95% confidence interval)
Countries
United States	10	84.1	0.0146	<0.001	1.034 (0.937–1.142)
Other	7	87.2	0.0529	<0.001	1.202 (0.981–1.473)
Study
Cohort study	11	81.4	0.0095	<0.001	0.979 (0.906–1.057)
Cross-sectional study	5	26.4	0.0085	0.246	1.266 (1.083–1.480)
Case-control study	1	–	0.0000	–	2.440 (1.728–3.446)
Sex
Male	5	57.2	0.0278	0.053	1.129 (0.919–1.388)
Female	8	60.0	0.0029	0.014	0.918 (0.867–0.973)
Fracture site
Any	11	80.9	0.0170	<0.001	1.032 (0.928–1.148)
Hip fracture	3	93.6	0.2743	<0.001	1.426 (0.769–2.643)
Other	3	94.6	0.0909	<0.001	1.125 (0.787–1.606)

Publication bias

Although we planned to assess publication bias, we did not perform the analysis owing to the limited number of studies (<10) included in the meta-analyses.

Discussion

In this meta-analysis, we aimed to evaluate the association between the DII and fracture risk in older adults. Data were extracted from eight studies with 462,986 participants. The results showed that highly pro-inflammatory diets were positively associated with fractures in older adults. The observed connection implicating diet-induced inflammation in fracture susceptibility aligns with the growing body of evidence indicating the multifactorial nature of bone health, where dietary patterns play a pivotal role.

In line with other epidemiologic studies, osteoporosis was independently predicted by fat consumption (pro-inflammatory load) in the Korean National Health and Nutrition Examination Survey IV.¹⁸ In the same study, higher loads of milk and cereal consumption in the diet were linked to a lower risk of low lumbar spine bone mineral density (BMD) in teenagers.¹⁹ In a case-cohort study involving 961 men, participants with the highest tumor necrosis factor (TNF) cytokine concentrations had a twofold greater risk of hip and symptomatic vertebral fractures, as well as a 40% to 60% increased risk of all non-spine fractures.²⁰ However, in contrast to our research, healthy eating seems to be more beneficial for bone health among older Chinese women. This may be connected to variations in the tools used to evaluate dietary quality as well as features of the study population.

The potential effect of a pro-inflammatory diet on bone disease can be interpreted through several biological mechanisms. Changes in bone metabolism have been associated with chronic systemic inflammation, which is often influenced by dietary habits.^21,22 Consuming pro-inflammatory foods over time may cause the body’s level of inflammation to increase. It has been proposed that consumption of a diet high in saturated fatty acids could potentially enhance the secretion of interleukin-1 (IL-1), IL-6, and TNF-α.²³ Red meat intake might result in concentrations of plasma CRP and other pro-inflammatory cytokines.²⁴ Moreover, these pro-inflammatory cytokines can stimulate osteoclast activity, which increases the risk of fracture by possibly decreasing BMD and promoting bone resorption.²⁵ Furthermore, the inflammatory milieu created by consuming a pro-inflammatory diet may disrupt the delicate balance between bone formation and resorption.²⁶ This dysregulation could impede the function of osteoblasts, the cells responsible for bone formation, ultimately compromising bone strength and quality.²⁷ Additionally, pro-inflammatory diets are often associated with comorbidities such as obesity, diabetes, and cardiovascular diseases, which themselves can impact bone health and fracture risk.²⁸ These health conditions may exacerbate systemic inflammation and weaken bones through various mechanisms, further increasing the propensity for fractures in older adults who adhere to pro-inflammatory dietary patterns.

Subgroup analyses were performed based on study design. The pooled results of five cross-sectional studies showed that the DII had a positive association with fracture risk (RR = 1.266, 95% CI: 1.083–1.480). However, a negative relationship with fracture risk was observed in the results of 11 cohort studies (RR = 0.979, 95% CI: 0.906–1.057). Moreover, high heterogeneity remained among cohort studies. Different study designs inherently harbor distinct biases that can ultimately affect the study outcomes.²⁹ For instance, cohort studies are susceptible to biases such as selection bias and loss to follow-up.^22,30 Conversely, cross-sectional studies are vulnerable in terms of selection bias, information bias, and confounding bias.³¹ In comparison with cohort studies, case–control and cross-sectional studies are more likely to include recall bias and selection bias, potentially compromising the accuracy of the results.³² Subgroup analysis in our study showed that relatively high heterogeneity was found in the included cohort studies. RCTs and high-quality clinical cohort studies could provide more reliable and convincing results.

Some limitations of this meta-analysis should be considered. First, older individuals commonly present concurrent symptoms or comorbidities stemming from age-related physiological decline. However, the studies encompassed in this analysis lacked systematic data collection concerning additional potential fracture risk factors. Their absence may curtail the precision of adjusting for confounding variables during multivariate analyses. Second, in the analysis of the relationship of the DII with fracture risk, our results showed statistically significant heterogeneity, probably owing to the variation in study designs. However, use of the random-effects model allowed us to consider the heterogeneity among studies. Third, this meta-analysis was conducted using published studies rather than individual data, which may have limited our ability to explore additional potential components and improve our understanding of the sources of heterogeneity.

Despite the above limitations, this study also has several strengths. Above all, this is the first meta-analysis to comprehensively assess the relationship between the DII and fractures in older adults. Moreover, both subgroup analysis and sensitivity analysis were used to detect potential sources of heterogeneity; sensitivity analysis and tests for publication bias can confirm the stability of the main outcomes.

Conclusion

The present meta-analysis indicated that diets high in pro-inflammatory components were significantly related to a higher risk of fractures in older adults. Transitioning to a diet with decreased consumption of pro-inflammatory foods and increasing the consumption of anti-inflammatory foods is suggested to prevent adverse fracture outcomes. Nevertheless, additional RCTs examining diets high in anti-inflammatory components are needed to establish causality and to determine whether dietary therapies can reduce the incidence of fractures.

Footnotes

Acknowledgements

We are grateful to all researchers in the enrolled studies.

Author contributions

Conceptualization: Xiaojuan Zheng, Wenhui Li

Data screen and extraction: ZhaoJie Su, Yonglong Yan

Data curation: Xiaojuan Zheng, Wenhui Li

Formal analysis: Yonglong Yan

Investigation: ZhaoJie Su

Methodology: Xiaojuan Zheng, Wenhui Li

Visualization: Xiaojuan Zheng, Wenhui Li

Writing – original draft: Xiaojuan Zheng, Wenhui Li

Writing – review & editing: Xuelin Huang

Data availability

The datasets generated during and/or analyzed during the current study are publicly available.

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Funding

ZhaoJie Su is supported by the Xiamen Municipal Natural Science Foundation (3502Z202373107). The remaining authors received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

ORCID iD

Xuelin Huang

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Association between the Dietary Inflammatory Index and fracture risk in older adults: a systematic review and meta-analysis

Abstract

Objective

Methods

Results

Conclusions

Keywords

Introduction

Methods

Search strategy

Inclusion and exclusion criteria

Literature screening and data extraction

Quality assessment

Data synthesis

Results

Literature search

Characteristics

Association of the DII and fracture risk in older adults

Subgroup analysis

Publication bias

Discussion

Conclusion

Footnotes

Acknowledgements

Author contributions

Data availability

Declaration of conflicting interest

Funding

ORCID iD

References