Systemic inflammation in midlife is associated with late-life functional limitations: The Atherosclerosis Risk in Communities Study

doi:10.21203/rs.3.rs-3794413/v1

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Systemic inflammation in midlife is associated with late-life functional limitations: The Atherosclerosis Risk in Communities Study

https://doi.org/10.21203/rs.3.rs-3794413/v1

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published 29 Jul, 2024

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Background

Functional limitations seriously affect the quality of life of individuals. Systemic inflammation generally coexists with functional limitations. This study aims to investigate the association between systemic inflammation in midlife and the risk of functional limitations in late-life.

Methods and Results

A total of 10,044 participants were included in a cohort study, with an average age of 53.9 ± 5.7 years at baseline. After a median follow-up time of 9.0 years, the prevalence of impaired activities of daily living (ADLs), instrumental activities of daily living (IADLs) and lower limb function (LEF) was 14.7%, 21.6%, and 50.3%, respectively. The values of four inflammatory biomarkers were used to calculate the state of inflammation composite score. Compared with the lowest quartile of the inflammation composite score, the highest quartile exhibited odds of impaired ADLs (OR = 1.589, 95% CI: 1.335–1.892), impaired IADLs (OR = 1.426, 95% CI: 1.228–1.657), and impaired LEF (OR = 1.728, 95% CI: 1.526–1.957). The association between systemic inflammation and functional limitations was partly mediated by cardiac and brain functions.

Conclusion

The present study showed that systemic inflammation in midlife was associated with a higher risk of late-life functional limitations. Protecting vital organ functions in midlife may reduce the risk of future functional limitations.

Trial registration: www.clinicaltrials.gov; Unique identifier: NCT00005131.

Health sciences/Medical research

Health sciences/Medical research/Experimental models of disease

Systemic inflammation

Functional limitations

Disability

ARIC study

Public health

Organ dysfunction

Functional limitations are defined as basic age-related physical dysfunction. Functional limitations include the ability to carry out self-care and domestic life activities, athletic ability and the ability to participate in social labor¹. In United States, approximately 20–30% of adults aged 60–69 have one or more functional limitations, while the proportion of adults aged 80 and above increases 2-fold^2,3. The number of the elderly with functional limitations will continue to increase with aging. Functional limitations are considered as a major precursor of disability^4,5, imposing a heavy burden on late-life quality of individuals and public healthcare services⁶. Functional limitations have been widely shown to be a key prognostic determinant of adverse outcomes^7–9. Therefore, we have an urgent front-burner to predict and prevent functional limitations, and find modifiable risk factors for targeted intervention.

Systemic inflammation refers to inflammation caused by infectious or non-infectious injury that can not be locally restricted by organisms¹⁰. Systemic inflammation and functional limitations share the common risk factors and pathophysiological pathways. It is widely accepted to use biomarkers of peripheral blood to describe the state of systemic inflammation. Several cross-sectional studies reported that high-level peripheral inflammatory biomarkers commonly coexists with functional limitations^11,12. Moreover, prospective studies have found that high-level peripheral inflammatory biomarkers were associated with functional limitations in the elderly^13,14. However, these studies were designed as cross-sectional studies or exhibited a short follow-up time. And advanced age interacts with high-level inflammatory biomarkers and a high incidence of functional limitations, which make these association can not well established. Moreover, previous studies only evaluate inflammation by single biomarkers, which could not accurately reflect the systemic inflammation status. Therefore, this study used composite biomarkers from the middle-aged populations to elucidate the causal relationship between inflammation.

A slew of studies have shown that several important inflammatory pathways are involved in the aging and injury of various organs^15,16, suggesting that inflammation may lead to impairment of physical function by damaging organ function. However, few studies have explored the impact of organ function on the relationship between inflammation and physical functional limitations. Therefore, our study aims to explore the association between mid-life systemic inflammation and late-life functional limitations, and whether this association is mediated by organ functions impairment.

2.1 Study Design and population

A prospective cohort study was conducted using the Atherosclerosis Risk in Communities (ARIC) study population from four communities in the United States¹⁷. A total of 15,792 participants, aged between 45 and 64 years, were recruited in 1987–1989 (Visit 1) and followed up every three years. Visit 2 was conducted in 1990–1992, Visit 3 in 1993–1995 and Visit 4 in 1996–1998. The ARIC study was approved by the institutional review committee of all participating institutions with the informed consent from all participants. Functional limitations were assessed for the first time in Visit 4. In our study, Visit 1 was regarded as the baseline, part of the data from Visit 2 was collected, and Visit 4 was regarded as the research outcome. Among participants in Visit 4 (n = 15,028), exclusion criteria were as follows: absence of an inflammatory biomarkers assessment (n = 336), absence of one or more covariates (n = 1111), and absence of an assessment on functional limitations (n = 3537). Finally, a total of 10,044 participants were enrolled in this study.

2.2 Inflammatory biomarkers

The physiological response of biomarkers to stress varies across individuals. One biomarker may be compensated by the effective function of other regions, and may not accurately describe the overall physiological function and the body's response to stress¹⁸. It is unclear whether a single measurement can adequately capture inflammation chronicity. Thus, the use of an inflammation composite score alleviated this possibility. Therefore, four biomarkers in plasma collected from Visit 1 were used to describe the state of systemic inflammation, including white blood cell count (after log-transformed for corrected skewness), von Willebrand factor, fibrinogen and Factor VIII. The inflammation composite score refers to the average value of four biomarkers after standardization to z-score. The selection of these markers is largely dependent on their availability in the ARIC study and that the inflammation composite score was often used in other studies¹⁹.

In this study, hypersensitive-C-reactive proteins (hs-CRP) in blood sample from Visit 1 and 2 was used as a sub-indicator of systemic inflammation. There was no difference between the relevant conditions of the two measurements. The hs-CRP was classified as “low” or “elevated”, with a cutoff value of 3.0 mg/L²⁰. According to the hs-CRP values from Visit 1 to Visit 2, the following four longitudinal patterns of change were established: (1) Consistent low hs-CRP: both were at low level; (2) Ascending hs-CRP: first at low level and then at elevated level; (3) Descending hs-CRP: first at elevated level and then at low level; (4) Consistent elevated hs-CRP: both were at elevated level.

2.3 Functional limitations

At Visit 4, the functional status assessment was completed in the form of a self-reported questionnaire containing the designated activities, as was done in the third National Health and Nutrition Examination Survey⁴. These activities included activities of daily living (eating, dressing, getting up, and walking)²¹, instrumental activities of daily living (cooking, housework, and financial management)²² and lower limb functions (standing up from a chair without arm support, bending or kneeling, walking 1/4 miles, going upstairs, and carrying 10 pounds)²³. Participants were required to indicate the level of difficulty in conducting these activities. When participants could not answer for themselves, proxies of participants could answer those questions with high degree of reliability. The final results were reported as "no limits" or "function impaired". Functional limitations were defined as three categories: impaired activities of daily living (ADLs), impaired instrumental activities of daily living (IADLs) and impaired lower limb function (LEF).

2.4 Assessment of Multiple Organ Function

Organ function was assessed at Visit 4, including cardiac function, brain function, lung function, liver function, and kidney function. Cardiac function was assessed using N-Terminal Pro-Brain Natriuretic Peptide (NT-proBNP), which was measured in plasma using electrochemiluminescence immunoassay on an automatic Cobase411 analyzer (Roche diagnosis). Brain function was assessed using the global composite cognition score, including delayed word recall test (DWRT), digit symbol substitution test (DSST), and word fluency test (WFT). The composite cognition score was the average value of the three tests after standardization to z-score^24–27. Lung function was assessed using the ratio of forced expiratory volume in one second / forced vital capacity (FEV1/FVC). The values were measured by the standardized Collins Survey II spirometer²⁸. Liver function was assessed using plasma alaninetransaminase (ALT). Kidney function was assessed using estimated glomerular filtration rate (eGFR) which was calculated using creatinine in the Eq. 2⁹.

2.5 Baseline Covariates

At baseline, the following covariates were assessed based on self-report or medical record evidence from participants: age, gender, race, income, education, hours of metabolic equivalent of task (MET-hour) per week, prevalence of medical comorbidity (hypertension, diabetes, coronary heart disease, heart failure, cancer, and chronic obstructive pulmonary disease), and medication use. Total cholesterol, high density lipoprotein, low density lipoprotein and triglycerides were measured by enzymatic analysis.

Hypertension was defined as blood pressure ≥ 140/90 mmHg, or a history of medication. Diabetes was defined as fasting glucose ≥ 126.0 mg/dl or non-fasting glucose ≥ 200.0 mg/dl, or a history of medication or insulin therapy. Coronary heart disease was defined as acute coronary syndrome, or chronic coronary artery disease, or a history of medication or coronary revascularization. Chronic obstructive pulmonary disease was identified as FEV1/FVC < 70% after bronchodilator, or a history of medication. Heart failure and cancer were diagnosed with the evidence from medical records.

2.6 Statistical analysis

In this study, continuous variables were represented with median (25th − 75th) or mean ± standard deviation, and categorical variables were represented with numbers (percentages). Continuous variables were compared using Mann–Whitney U test or ANOVA, and categorical variables were compared using chi-square test.

Logistic regression models were conducted to assess the association between the inflammation composite score at Visit 1, hs-CRP at Visit 1, and longitudinal pattern of hs-CRP (from Visit 1 to Visit 2) with functional limitations (impaired ADLs, IADLs and LEF), respectively. Two regression models were established to examine the independent role of these relationships. Model 1 was adjusted according to age, gender, race, education, income, and MET-hour/week. Model 2 was additionally adjusted according to the prevalent of hypertension, diabetes, coronary heart disease, heart failure, cancer, chronic obstructive pulmonary disease, total cholesterol, high density lipoprotein, low density lipoprotein, triglycerides, cholesterol-lowering and anti-inflammatory medications. Furthermore, a logistic regression analysis in Model 2 was conducted to assess the effect modification between the inflammation composite score and functional limitations of age, gender and race subgroups. The value of multiplicative interaction term < 0.05 was considered statistically significant.

According to the procedure recommended by Hayes³⁰, Pathway analysis was carried out through the structural equation Model 4 to calculate the indirect effects of the inflammation composite score on functional limitations, including cardiac function (NT-proBNP was log-transformed to correct for skewness), brain function (composite cognition score), lung function (FEV1/FVC), liver function (ALT), and kidney function (eGFR). In structural equation modeling, cross-products from estimated mediation effects were considered statistically significant when confidence intervals (CIs) did not include zero. Our study used the standardized regression coefficients (β) to report point estimates of direct and indirect effects.

A two-tailed P value of < 0.05 was considered statistically significant. SPSS Statistics (version 36.0, IBM Corp, Armonk, USA), PROCESS (version 3.5 for SPSS) and R software (version 3.5.0, Vienna, Austria) were used for data analysis.

3.1 Baseline characteristics

The 10,044 participants with an average age of 53.9 ± 5.7 years were categorized into quartiles (Q1, Q2, Q3 and Q4) based on the inflammation composite score. Table 1 shows the baseline participant characteristics. Increased inflammation composite score was associated with aging, female, African American (still lower than Caucasians), lower income and education levels, unhealthy behaviors, higher levels of cardiovascular biomarkers, and higher odds of complications (P < 0.001 for all).

Table 1

Baseline participant characteristics stratified by groups of inflammation composite score at Visit 1 (1987–1989).
Characteristic		Inflammation Composite Score				P
Characteristic		Q1	Q2	Q3	Q4	P
	N	2511	2511	2511	2511
Demographic Variables
	Age, years	52.7 ± 5.5	53.7 ± 5.6	54.4 ± 5.8	55.0 ± 5.7	< 0.001
	Female	1323(52.7)	1363(54.3)	1363(54.3)	1477(58.8)	< 0.001
	Race (African American)	414(16.5)	434(17.3)	537(21.4)	723(28.8)	< 0.001
	Income, US$					< 0.001
	<16 000	267(10.6)	354(14.1)	469(18.7)	608(24.2)
	16 000–35 000	825(32.9)	880(35.1)	882(35.1)	988(39.4)
	>35 000	1419(56.5)	1277(50.9)	1160(46.2)	915(36.4)
	Education					< 0.001
	Less than high school	298(11.9)	416(16.6)	513(20.4)	659(26.2)
	High school	782(31.1)	803(32.0)	792(31.5)	810(32.3)
	College	1431(57.0)	1292(51.5)	1206(48.0)	1042(41.5)
	Smoking					< 0.001
	Never	1267(50.5)	1170(46.6)	1074(42.8)	925(36.8)
	Ever	953(38.0)	856(34.1)	811(32.3)	772(30.7)
	Current	291(11.6)	485(19.3)	626(24.9)	814(32.4)
	Drinking					< 0.001
	Never	513(20.4)	565(22.5)	650(25.9)	692(27.6)
	Ever	339(13.5)	398(15.9)	434(17.3)	521(20.8)
	Current	1659(66.1)	1548(61.7)	1427(56.8)	1298(51.7)
	MET-hour, /week	16.8 ± 18.9	15.4 ± 18.3	14.6 ± 18.0	12.3 ± 16.5	< 0.001
Physiological & Lab Variables
	Body mass index, kg/m²	26.1 ± 4.1	26.9 ± 4.5	27.9 ± 5.2	29.1 ± 6.0	< 0.001
	SBP, mmHg	116.8 ± 16.3	119.0 ± 17.7	119.9 ± 17.3	122.0 ± 18.0	< 0.001
	DBP, mmHg	72.7 ± 10.5	72.8 ± 10.8	73.2 ± 10.7	73.6 ± 10.9	0.015
	Total cholesterol, mmol/l	5.4 ± 1.0	5.5 ± 1.0	5.6 ± 1.1	5.6 ± 1.1	< 0.001
	HDL-C, mmol/l	1.4 ± 0.5	1.4 ± 0.4	1.3 ± 0.4	1.3 ± 0.4	< 0.001
	LDL-C, mmol/l	3.4 ± 1.0	3.5 ± 1.0	3.6 ± 1.0	3.7 ± 1.0	< 0.001
	Triglycerides, mmol/l	1.3 ± 0.7	1.4 ± 0.7	1.5 ± 0.7	1.5 ± 0.8	< 0.001
	Creatinine, mg/dl	0.7 ± 0.2	0.7 ± 0.3	0.8 ± 0.4	0.8 ± 0.6	< 0.001
	Blood glucose,mmol/l	5.5 ± 1.1	5.7 ± 1.3	5.8 ± 1.7	6.4 ± 2.5	< 0.001
Chronic Medical Conditions
	Hypertension	478(19.0)	579(23.1)	656(26.1)	880(35.1)	< 0.001
	Diabetes mellitus	66(2.6)	110(4.4)	182(7.3)	360(14.3)	< 0.001
	Coronary heart disease	48(1.9)	76(3.0)	83(3.3)	140(5.6)	< 0.001
	Heart Failure	45(1.8)	68(2.7)	76(3.0)	135(5.4)	< 0.001
	Cancer	111(4.4)	128(5.1)	138(5.5)	145(5.8)	0.153
	Chronic Obstructive Pulmonary Disease	74(3.0)	81(3.2)	118(4.7)	157(6.3)	< 0.001
Medication
	Anti-inflammatory (regular use)	1172(46.7)	1212(48.3)	1103(43.9)	1196(47.6)	0.011
	Cholesterol lowering (last 2 weeks)	53(2.1)	60(2.4)	69(2.8)	87(3.5)	0.018
Values are displayed as N (%) for categorical and mean ± SD for continuous variable.
MET, metabolic equivalent of task; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol.

3.2 Inflammation and functional limitations

After a median follow-up time of 9.0 years, the prevalence of impaired ADLs, IADLs and LEF was 14.7%, 21.6%, and 50.3%, respectively. The higher the inflammation composite score, the higher risk of functional limitations after approximately 9 years (P < 0.001, Fig. 1). In the adjusted logistic regression model, compared with Q1 with a low inflammation composite score, Q4 exhibited a higher odds of impaired ADLs (OR = 1.589, 95% CI: 1.335–1.892, p < 0.001), impaired IADLs (OR = 1.426, 95% CI: 1.228–1.657, p < 0.001), and impaired LEF (OR = 1.728, 95% CI: 1.526–1.957, p < 0.001). Notably, the odds ratio of impaired ADLs and impaired LEF showed an gradually upward trend with the increase of inflammation composite score (Table 2).

Table 2

Adjusted odds ratios (OR) for the association of inflammation composite score with impaired activities of daily living (ADLs), instrumental ADLs (IADLs), and lower-extremity function (LEF) .
HLS	Unadjusted		Model 1		Model 2
HLS	OR (95%CI)	P	OR (95%CI)	P	OR (95%CI)	P
Impaired ADLs		< 0.001		< 0.001		< 0.001
Q1	Ref.	-	Ref.	-	Ref.	-
Q2	1.347 (1.131–1.604)	0.001	1.247 (1.046–1.488)	0.014	1.212 (1.013–1.450)	0.036
Q3	1.594 (1.344–1.889)	< 0.001	1.393 (1.172–1.656)	< 0.001	1.319 (1.105–1.574)	0.002
Q4	2.341 (1.991–2.753)	< 0.001	1.857 (1.571–2.195)	< 0.001	1.589 (1.335–1.892)	< 0.001
Impaired IADLs		< 0.001		< 0.001		< 0.001
Q1	Ref.	-	Ref.	-	Ref.	-
Q2	1.410 (1.220–1.630)	< 0.001	1.286 (1.109–1.492)	0.001	1.238 (1.065–1.439)	0.005
Q3	1.452 (1.256–1.677)	< 0.001	1.223 (1.055–1.419)	0.008	1.135 (0.975–1.321)	0.104
Q4	2.233 (1.945–2.564)	< 0.001	1.676 (1.452–1.936)	< 0.001	1.426 (1.228–1.657)	< 0.001
Impaired LEF		< 0.001		< 0.001		< 0.001
Q1	Ref.	-	Ref.	-	Ref.	-
Q2	1.422 (1.271–1.591)	< 0.001	1.315 (1.170–1.478)	< 0.001	1.271 (1.129–1.431)	< 0.001
Q3	1.835 (1.641–2.054)	< 0.001	1.603 (1.425–1.802)	< 0.001	1.489 (1.321–1.679)	< 0.001
Q4	2.580 (2.302–2.890)	< 0.001	2.001 (1.775–2.255)	< 0.001	1.728 (1.526–1.957)	< 0.001
Model 1: adjusted by age, sex, race, education (< high school, high school, or > high school), annual household income (< 16 000, 16 000 to 35 000, > 35 000), and physical activity defined by MET-hour/week.
Model 2: adjusted by model 1 plus, prevalent of hypertension, diabetes, coronary heart disease, heart failure, cancer, chronic obstructive pulmonary disease, total cholesterol, high density lipoprotein, low density lipoprotein, triglycerides, cholesterol-lowering and anti-inflammatory medication use.
Unexplained variables are regarded as continuous variables. OR, odds ratio; CI, confidence interval.

In the adjusted logistic regression model, compared with the group with low hs-CRP level at Visit 1, participants initially with elevated hs-CRP had a higher odds of activities of impaired ADLs (OR = 2.076, 95% CI: 1.829–2.357, p < 0.001), impaired IADLs (OR = 1.741, 95% CI: 1.561–1.941, p < 0.001), and impaired LEF (OR = 1.884, 95% CI: 1.719–2.066, p < 0.001) (Fig. 2). Furthermore, longitudinal pattern of changes in hs-CRP affected late-life functional limitations. In the adjusted logistic regression model, compared with consistent low hs-CRP, participants with ascending hs-CRP, descending hs-CRP, and consistent elevated hs-CRP exhibited a higher risk of functional limitations, respectively (Fig. 3).

3.3 Subgroup Analysis

Figure 4 showed a significant interaction between races (P for interaction: 0.016, 0.004 and 0.037, respectively). Compared with African Americans, Caucasians had a higher risk of mid-life inflammation composite score associated with late-life functional limitations. For participants aged < 54 years, the inflammation composite score revealed a higher risk associated with impaired LEF (P for interaction = 0.002), and the risk associated with impaired ADLs was higher but not significant(P for interaction = 0.059). The association between inflammation composite score and functional limitations was consistent among the gender subgroups (P for interaction > 0.05).

3.4 Path analysis

Path analysis showed that the inflammation composite score and functional limitations were significantly associated with NT-proBNP and composite cognition score (p < 0.01). FEV1/FVC, ALT and eGFR were not shown as mediators. Table 3 showed pathway estimates and 95% CIs of the mediation model. Figure 5 showed the effects of inflammation composite score on impaired ADLs, impaired IADLs, and impaired LEF was partly mediated by NT-proBNP (5.8%, 9.3%, and 7.2%; respectively) and composite cognition score (19.5%, 28.2%, and 14.3%; respectively).

Table 3

Direct and indirect effects of inflammation composite score on impaired activities of daily living (ADLs), instrumental ADLs (IADLs), and lower-extremity function (LEF) .
Effect	Variables	Impaired ADLs			Impaired IADLs			Impaired LEF
Effect	Variables	β coefficient	95%CI	SE	β coefficient	95%CI	SE	β coefficient	95%CI	SE
Direct	inflammation composite score	0.349	0.263–0.435	0.044	0.275	0.199–0.352	0.039	0.461	0.394–0.528	0.034
Indirect	NT-proBNP	0.027	0.010–0.098	0.014	0.041	0.026–0.104	0.013	0.042	0.021–0.089	0.021
Indirect	Composite cognition score	0.091	0.027–0.189	0.078	0.124	0.086–0.173	0.096	0.084	0.032–0.125	0.060
NT-proBNP, N-terminal pro-B-type natriuretic peptide; CI, confidence interval; SE, standard error.

In this study, participants with a higher level of mid-life systemic inflammation exhibited a gradually increasing risk of late-life functional limitations. Assuming causality, participants with a higher overall inflammation composite score may have a 40–70% increased risk of adverse outcomes after approximately 9 years. Higher hs-CRP levels may increase the risk of late-life functional limitations by nearly 2-folds.

The pattern of consistently elevated or increasing or descending hs-CRP, associated with an increased chance of functional limitation compared to consistently low levels. In the present study, individuals with elevated hs-CRP lasting 3 years were at the greatest risk, followed by individuals with initially low hs-CRP and elevated 3 years later, which supported the hypothesis that long-term inflammation is an independent etiological role for functional limitations^31–33. Furthermore, in addition to existing systemic inflammation, underlying long-term inflammation may play a role in the development of physiological functional limitations³⁴.

Subgroup analysis demonstrated that the association between inflammation composite score and functional limitations was consistent irrespective of gender. However, this association was stronger among Caucasians than African Americans. There has been little research on the underlying factors that contribute to functional limitations caused by inflammation in African Americans. Racial differences in the regulation of inflammatory signaling pathways³⁵, chronic disease burden, and non-physiological factors (such as socio-economic status, healthcare access and affordability)³⁶ may explain the race-based differences observed in this study. More importantly, systemic inflammation at a relatively young age exhibited a higher risk of functional limitation a few years later, suggesting that early exposure to systemic inflammation has a higher risk of functional limitations. Furthermore, the morbidity of multiple chronic diseases shows an accelerated trend in midlife. In our study, adjusting medical comorbidities played a strongly weakening effect on the association between systemic inflammation and functional limitations. Mid-life inflammation may serve as an important common biological mechanism of late-life multimorbidity and functional limitations³⁷.

Systemic inflammation may lead to diseases of various important organs, such as heart, brain, lung, liver, and kidney^33,38. Previous studies have demonstrated that cardiac function has been independently associated with functional limitations, and brain function may be a stronger predictor^39–42. The relationship between other systemic diseases and functional limitations has not been proved to be independent. According to our findings, the increased risk of functional limitations caused by systemic inflammation may be mediated by cardiac function and brain function. Lung, liver, and kidney are not involved in this pathway. Indirect effects mediated by cardiac function and brain function accounted for 5–10% and 14–28%, respectively. In general, systemic inflammation partially causes functional limitations through the heart and brain, which can reveal important intervention and therapy targets. Investigators should consider planning preventive programs to protect the heart and brain functions of middle-aged individuals with systemic inflammation, so as to reduce the risk of functional limitations and even disability.

There are several limitations in this study. First, in addition to the inflammatory biomarkers used in this study participating in systemic inflammatory responses, some biomarkers are also involved in other biological regulation pathways, leading to the failure of inflammation compound score to fully represent the mechanism of systemic inflammation. Second, functional impaired status in the study was measured only at Visit 4 and not at baseline, and thus cannot demonstrate causality. Third, the midlife hs-CRP pattern from Visit 1 to visit 2 was not fully representative of the overall follow-up trend. Fourth, important parameters were selected for each organ function, but the assessment was not sufficiently comprehensive. Fifth, in pathway analysis, only the effects of vital organ function have been studied without assessing the motor system, which may account for a certain proportion of the pathway.

In this study individuals with mid-life systemic inflammation were at increased risk of late-life functional limitations. The association, which was stronger in Caucasians and relatively younger ages, was partly mediated by cardiac and brain function. For individuals with systemic inflammation, protection on heart and brain function in midlife may be conducive to reducing the risk of functional limitations and improving quality of life in the future.

Ethical statement

This study was conducted in conformity to the Declaration of Helsinki and was approved by the Human Ethical Committee of West China Hospital of Sichuan University. The ARIC study was approved by the institutional review committee of all participating institutions with the informed consent from all participants.

Funding

This work was supported financially by grants from Sichuan Science and Technology Program (No. 2023YFS0027, 2023YFS0240, 2023YFS0074, 2023NSFSC1652, 2022YFS0279, 2021YFQ0062, 2022JDRC0148), Sichuan Provincial Health Commission (No. ZH2022-101), Sichuan University West China Nursing Discipline Development Special Fund Project (No. HXHL21016)

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://biolincc.nhlbi.nih.gov/home/.

Author contribution

YT and YJ conceived the study design. YT, YJ and AG collected the epidemiological and clinical data. YT, YJ, FL, and AG summarized data and performed the statistical analysis. YT and YJ interpreted the data and drafted the manuscript. RZ participated in the design of the study, acquired the data, and helped to revise the manuscript. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. All authors contributed to the article and approved the submitted version.

Acknowledgments

The authors thank the staff and participants of the ARIC study and BioLINCC for their important contributions.

Disclosure

The authors report no disclosures relevant to the manuscript.

Freedman, V. A. Adopting the ICF language for studying late-life disability: a field of dreams? J Gerontol A Biol Sci Med Sci 64, 1172-1174; discussion 1175-1176 (2009).
Holmes, J., Powell-Griner, E., Lethbridge-Cejku, M. & Heyman, K. Aging differently: Physical limitations among adults aged 50 years and over: United States, 2001-2007. NCHS Data Brief, 1-8 (2009).
Ervin, R. B. Prevalence of functional limitations among adults 60 years of age and over: United States, 1999-2002. Adv Data, 1-7 (2006).
Ostchega, Y., Harris, T. B., Hirsch, R., Parsons, V. L. & Kington, R. The prevalence of functional limitations and disability in older persons in the US: data from the National Health and Nutrition Examination Survey III. J Am Geriatr Soc 48, 1132-1135 (2000).
Jette, A. M. Toward a common language of disablement. J Gerontol A Biol Sci Med Sci 64, 1165-1168 (2009).
Bentley, J. P. et al. Functional status, life-space mobility, and quality of life: a longitudinal mediation analysis. Qual Life Res 22, 1621-1632 (2013).
McCusker, J., Kakuma, R. & Abrahamowicz, M. Predictors of functional decline in hospitalized elderly patients: a systematic review. J Gerontol A Biol Sci Med Sci 57, M569-577 (2002).
Rozzini, R. et al. Relationship between functional loss before hospital admission and mortality in elderly persons with medical illness. J Gerontol A Biol Sci Med Sci 60, 1180-1183 (2005).
Koroukian, S. M. et al. Combinations of Chronic Conditions, Functional Limitations, and Geriatric Syndromes that Predict Health Outcomes. J Gen Intern Med 31, 630-637 (2016).
Marker-Hermann, E. [Systemic inflammation]. Internist (Berl) 54, 397-398 (2013).
Cohen, H. J., Pieper, C. F., Harris, T., Rao, K. M. & Currie, M. S. The association of plasma IL-6 levels with functional disability in community-dwelling elderly. J Gerontol A Biol Sci Med Sci 52, M201-208 (1997).
Ferrucci, L. et al. Serum IL-6 level and the development of disability in older persons. J Am Geriatr Soc 47, 639-646 (1999).
Penninx, B. W. et al. Inflammatory markers and incident mobility limitation in the elderly. J Am Geriatr Soc 52, 1105-1113 (2004).
Pieper, C. F., Rao, K. M., Currie, M. S., Harris, T. B. & Cohen, H. J. Age, functional status, and racial differences in plasma D-dimer levels in community-dwelling elderly persons. J Gerontol A Biol Sci Med Sci 55, M649-657 (2000).
McGeer, P. L. & McGeer, E. G. Inflammation and the degenerative diseases of aging. Ann N Y Acad Sci 1035, 104-116 (2004).
Prasad, S., Sung, B. & Aggarwal, B. B. Age-associated chronic diseases require age-old medicine: role of chronic inflammation. Prev Med 54 Suppl, S29-37 (2012).
The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. Am J Epidemiol 129, 687-702 (1989).
Juster, R. P., McEwen, B. S. & Lupien, S. J. Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci Biobehav Rev 35, 2-16 (2010).
Walker, K. A. et al. Midlife systemic inflammatory markers are associated with late-life brain volume: The ARIC study. Neurology 89, 2262-2270 (2017).
Biasucci, L. M., Cdc & Aha. CDC/AHA Workshop on Markers of Inflammation and Cardiovascular Disease: Application to Clinical and Public Health Practice: clinical use of inflammatory markers in patients with cardiovascular diseases: a background paper. Circulation 110, e560-567 (2004).
Nagi, S. Z. An epidemiology of disability among adults in the United States. Milbank Mem Fund Q Health Soc 54, 439-467 (1976).
Rosow, I. & Breslau, N. A Guttman health scale for the aged. J Gerontol 21, 556-559 (1966).
Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A. & Jaffe, M. W. Studies of Illness in the Aged. The Index of Adl: A Standardized Measure of Biological and Psychosocial Function. JAMA 185, 914-919 (1963).
Li, D. et al. Plasma phospholipid very-long-chain SFAs in midlife and 20-year cognitive change in the Atherosclerosis Risk in Communities (ARIC): a cohort study. Am J Clin Nutr 111, 1252-1258 (2020).
Knopman, D. S. & Ryberg, S. A verbal memory test with high predictive accuracy for dementia of the Alzheimer type. Arch Neurol 46, 141-145 (1989).
Jaeger, J. Digit Symbol Substitution Test: The Case for Sensitivity Over Specificity in Neuropsychological Testing. J Clin Psychopharmacol 38, 513-519 (2018).
Pendleton, M. G., Heaton, R. K., Lehman, R. A. & Hulihan, D. Diagnostic utility of the Thurstone Word Fluency Test in neuropsychological evaluations. J Clin Neuropsychol 4, 307-317 (1982).
Rabe, K. F. et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 176, 532-555 (2007).
Parrinello, C. M. et al. Recalibration of blood analytes over 25 years in the atherosclerosis risk in communities study: impact of recalibration on chronic kidney disease prevalence and incidence. Clin Chem 61, 938-947 (2015).
Igartua, J. J. & Hayes, A. F. Mediation, Moderation, and Conditional Process Analysis: Concepts, Computations, and Some Common Confusions. Span J Psychol 24, e49 (2021).
Singh, T. & Newman, A. B. Inflammatory markers in population studies of aging. Ageing Res Rev 10, 319-329 (2011).
Mekli, K., Nazroo, J. Y., Marshall, A. D., Kumari, M. & Pendleton, N. Proinflammatory genotype is associated with the frailty phenotype in the English Longitudinal Study of Ageing. Aging Clin Exp Res 28, 413-421 (2016).
Furman, D. et al. Chronic inflammation in the etiology of disease across the life span. Nat Med 25, 1822-1832 (2019).
Candore, G., Caruso, C. & Colonna-Romano, G. Inflammation, genetic background and longevity. Biogerontology 11, 565-573 (2010).
Quinones, A. R. et al. Racial/ethnic differences in multimorbidity development and chronic disease accumulation for middle-aged adults. PLoS One 14, e0218462 (2019).
Mahajan, S. et al. Trends in Differences in Health Status and Health Care Access and Affordability by Race and Ethnicity in the United States, 1999-2018. JAMA 326, 637-648 (2021).
Friedman, E. M., Christ, S. L. & Mroczek, D. K. Inflammation Partially Mediates the Association of Multimorbidity and Functional Limitations in a National Sample of Middle-Aged and Older Adults: The MIDUS Study. J Aging Health 27, 843-863 (2015).
Liberale, L. et al. Inflammation, Aging, and Cardiovascular Disease: JACC Review Topic of the Week. J Am Coll Cardiol 79, 837-847 (2022).
Dodge, H. H. et al. Cognitive impairment as a strong predictor of incident disability in specific ADL-IADL tasks among community-dwelling elders: the Azuchi Study. Gerontologist 45, 222-230 (2005).
Stuck, A. E. et al. Risk factors for functional status decline in community-living elderly people: a systematic literature review. Soc Sci Med 48, 445-469 (1999).
Kelly-Hayes, M., Jette, A. M., Wolf, P. A., D'Agostino, R. B. & Odell, P. M. Functional limitations and disability among elders in the Framingham Study. Am J Public Health 82, 841-845 (1992).
Tas, U. et al. Incidence and risk factors of disability in the elderly: the Rotterdam Study. Prev Med 44, 272-278 (2007).

No competing interests reported.

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Systemic inflammation in midlife is associated with late-life functional limitations: The Atherosclerosis Risk in Communities Study

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Abstract

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1. Introduction

2. Methods

2.1 Study Design and population

2.2 Inflammatory biomarkers

2.3 Functional limitations

2.4 Assessment of Multiple Organ Function

2.5 Baseline Covariates

2.6 Statistical analysis

3. Results

3.1 Baseline characteristics

3.2 Inflammation and functional limitations

3.3 Subgroup Analysis

3.4 Path analysis

4. DISCUSSION

5. Limitations

6. Conclusions

Declarations

References

Additional Declarations

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