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. 2020 Jan:134:105269.
doi: 10.1016/j.envint.2019.105269. Epub 2019 Nov 25.

Air pollution, noise exposure, and metabolic syndrome - A cohort study in elderly Mexican-Americans in Sacramento area

Affiliations

Air pollution, noise exposure, and metabolic syndrome - A cohort study in elderly Mexican-Americans in Sacramento area

Yu Yu et al. Environ Int. 2020 Jan.

Abstract

Background: Previous studies suggested that air pollutants may increase the incidence of metabolic syndrome, but the potential impact from traffic sources is not well-understood. This study aimed to investigate associations between traffic-related nitrogen oxides (NOx) or noise pollution and risk of incident metabolic syndrome and its components in an elderly Mexican-American population.

Methods: A total of 1,554 Mexican-American participants of the Sacramento Area Latino Study on Aging (SALSA) cohort were followed from 1998 to 2007. We used anthropometric measures and biomarkers to define metabolic syndrome according to the recommendations of the Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP ATP III). Based on participants' residential addresses at baseline, estimates of local traffic-related NOx were generated using the California Line Source Dispersion Model version 4 (CALINE4), and of noise employing the SoundPLAN software package. We used Cox regression models with calendar time as the underlying time scale to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations of air pollution or noise with metabolic syndrome or its components.

Results: Each per unit increase of traffic-related NOx (2.29 parts per billion (ppb)) was associated with a 15% (HR = 1.15, 95% CI: 1.04-1.28) lower level of high-density lipoprotein cholesterol (HDL-cholesterol), and each 11.6 decibels (dB) increase in noise increased the risk of developing metabolic syndrome by 17% (HR = 1.17, 95% CI: 1.01-1.35).

Conclusion: Policies aiming to reduce traffic-related air pollution and noise might mitigate the risk of metabolic syndrome and its components in vulnerable populations.

Keywords: Air pollution, noise; Metabolic syndrome; Mexican-Americans.

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Conflict of interest statement

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1.
Figure 1.. Effect estimates (and 95% confidence intervals) from adjusted Cox models for annual average of 24-hour (A) or nighttime noise (B) exposure at a quartile-based scale levels and the risk of metabolic syndrome or each individual component.
(A) 24-hour noise level was divided into 4 categories (<65 dB, 65–70 dB, 70–75 dB, and ≥75 dB) according to (rounded) quartile values. The reference group included those with 24-hour average noise exposure <65 dB. P-value for trend are 0.02 for metabolic syndrome, 0.40 for abdominal obesity, 0.05 for hypertension, 0.81 for hyperglycemia, 0.21 for hypertriglyceridemia and 0.03 for low HDL-cholesterol. (B) Nighttime noise level was divided into 4 categories (<55 dB, 55–60 dB, 60–65 dB, and ≥65 dB). The reference group included those with nighttime noise exposure <55 dB. P-value for trend are 0.01 for metabolic syndrome, 0.34 for abdominal obesity, 0.09 for hypertension, 0.63 for hyperglycemia, 0.16 for hypertriglyceridemia and 0.03 for low HDL-cholesterol. Definitions for metabolic syndrome and each individual symptom: (i) abdominal obesity: waist circumference of ≥ 40 inches in men; ≥ 35 inches in women); (ii) borderline elevation of blood glucose (fasting glucose ≥ 100 mg/dl, or use of glucose-lowering medications; (iii) elevated blood pressure (≥ 140/90 mmHg), or use of anti-hypertensive medication; (iv) elevated triglycerides (≥ 150 mg/dl), or use of statins; and (v) low high-density lipoprotein (HDL) cholesterol (men: < 40 mg/dl; women: < 50mg/dl), or use of statins. Metabolic syndrome was defined as the presence of three or more of these components. All models were adjusted for baseline age, gender, years of education, neighborhood socioeconomic status indicator, occupation during most of life, baseline smoking status, baseline alcohol consumption status and physical activity level. The dashed lines display the 95% confidence intervals.

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