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Air Quality and Pace of Aging among Older Adults in the United States

Investigators:

Arun Balachandran, Daniel W Belsky

Funding:

NIA R61AG086854 (CACHE)

Data sources:

Measures:

  • Health Measures: The Pace of Aging health measures used in the study is obtained from three blood biomarkers (HbA1c, C-reactive protein, cystatin-C), three physical assessments (diastolic blood pressure, peak-flow lung-function testing, waist circumference), and three functional tests (gait speed, balance, grip strength) available in the US Health and Retirement Study.
  • Aging Measures: Pace of Aging Age for all participants in HRS 2006-2016 who has at least two follow-ups of biomarker data (N=13, 358).
  • Climate Measures: Annual data of 5 exposure during 2002-16.

Project Summary:

Air pollution is emerging as a central public health threat to aging populations. Living in more polluted areas is associated with increased risk for a wide range of aging related diseases. There is emerging evidence that air pollution may accelerate the aging process itself, shortening healthy lifespans in already aging populations. Efforts are underway to reduce pollution and its harms. Metrics to monitor the impact of those efforts on population health are needed. Passively accumulated data such as hospitalizations for asthma or heart attacks are limited because they capture only the tip of the iceberg of latent morbidity caused by pollution. More sensitive and comprehensive measures are needed. If air pollution really does hasten the aging process, new methods to quantify the pace of biological aging could provide the answer.

The central hypothesis of this pilot proposal is that air pollution accelerates the pace of biological aging. We propose a one-year study to test this hypothesis and generate proof-of-concept for a method to monitor population health impacts of air pollution and efforts to reduce/mitigate it. Successful completion of this pilot study will position us to apply for R01 grants to expand our project to global scale, to develop an interactive toolkit for researchers and policymakers can use to evaluate how changes in air pollution levels will impact population aging, and to investigate the role of air pollution in social gradients in biological aging in the US.

Our pilot will analyze data from the US Health and Retirement Study (HRS), an ongoing longitudinal study of adults aged 50 and older and their spouses in the United States. HRS is ongoing since 1992. Survey data are collected every two years. Since 2006, biomarker data are collected every four years. Refresher panels are recruited periodically to replace study members who have died. The HRS has so far collected data on around 40,000 individuals, with roughly 20,00 participating at any given assessment wave. Our analysis will focus on a sample of 13,000 adults for whom we have previously conducted analysis to phenotype Pace of Aging, a longitudinal measurement of the rate of decline in the integrity of multiple bodily systems2. We will link Pace of Aging, sociodemographic, and morbidity and mortality data with small-area air pollution data within the HRS Contextual Data Resource (HRS-CDR) hosted within the Michigan Center for Demography of Aging (MiCDA) accessed via their Virtual Desktop Infrastructure (VDI). HRS-CDR is a collection of analysis-ready datasets that link HRS participant-level data with small-area characteristics relevant to health and wellbeing. Air pollution exposure data consist of average annual concentrations of PM 2.5 (mg/m3) and O3 (mg/m3) at the census-tract level for the period 2002-2016.

On the creation of the weather variables:

The air pollution data are integrated at the census-tract level, within the server of the Health and Retirement Study at Michigan Centre on Demography of Aging (MiCDA). The Virtual Data Enclave (VDE) supported by MiCDA gives the PM 2.5 (mg/m3) and O3 (mg/m3) at the census-tract level for the period 2002-2016, and the researchers made use of this.

Outputs:

  • Poster
  • Future publications and code