About

Ping-hsiu Alice Lin is an Assistant Professor in the Department of Anthropology at Harvard University, based in the Tozzer Anthropology Building in Cambridge, MA. Her research interests encompass Political and Economic Anthropology, focusing on value, commodification, labor and capital, expertise and tacit knowledge, and the history of geosciences. She is currently working on a book project titled 'Precious Economies,' which examines contemporary efforts to render minerals into precious stones through labor, science, and artisanship within the gemstone industry in Pakistan and beyond. Her work draws upon multi-sited fieldwork and archival research to explore how the valuation of gems is intertwined with imperial circuits of extraction and commerce, as well as recent developments in expertise related to provenance and qualities. Her research elucidates the material economy of precious commodities and how it extends across different people and sites of trade and production in Asia.

Research topics

• Medicine
• Obstetrics
• Biology
• Genetics
• Andrology
• Physiology
• Internal medicine
• Bioinformatics
• Environmental health

Selected publications

• Comparative BMI-z Changes With Initiation and Adherence to Antidepressant Medications Among Youth

  Journal of the American Academy of Child & Adolescent Psychiatry · 2025-11-01 · 2 citations

  article
  PublisherDOI

• Emulation of a Target Trial of Antihypertensive Medications on Weight Change

  Journal of General Internal Medicine · 2025-09-29

  articleOpen access1st authorCorresponding

  BACKGROUND: Weight gain after starting antihypertensive medications is a frequent concern for patients, but there is limited data on expected weight change after initiation of these medications. A comparative effectiveness trial to evaluate this outcome would not be feasible. OBJECTIVE: To estimate and compare average weight change under initiating and adhering to commonly prescribed, first-line antihypertensive medications as monotherapy by emulating a target trial. DESIGN: Retrospective observational cohort study over 24 months of follow-up using electronic health records (EHR). PARTICIPANTS: 141,260 patients prescribed one of seven antihypertensives between 2010 and 2019 across 8 US health systems. MAIN OUTCOME AND MEASURES: We examined mean weight change associated with initiation of and adherence to amlodipine, atenolol, hydrochlorothiazide, losartan, metoprolol, or propranolol, relative to lisinopril, at 6, 12, and 24 months after initiation. To adjust for baseline confounding and informative outcome measurement, we used inverse probability weighting with repeated outcome marginal structural models. KEY RESULTS: After baseline and time-varying covariate adjustment, initiation of and adherence to lisinopril were associated with mean weight loss at 6 months (- 0.69 kg, 95% CI - 0.92, - 0.47), 12 months (- 0.58 kg, 95% CI - 1.05, - 0.30), and 24 months (- 1.121 kg, 95% CI - 2.013, - 0.46). Compared to lisinopril, the estimated 6-month weight change was higher for patients prescribed hydrochlorothiazide (0.68 kg, 95% CI 0.31, 1.04), losartan (0.54 kg, 95% CI 0.17, 0.93), metoprolol (1.38 kg, 95% CI 0.95, 1.76), and propranolol (1.03 kg, 95% CI 0.346, 1.62). At 12 months, metoprolol (1.74 kg, 95% CI 1.03, 2.41) and propranolol (1.72 kg, 95% CI 0.06, 3.235) continued to show higher weight change compared to lisinopril. CONCLUSION: We observed small differences in weight change across antihypertensive medications, with lisinopril leading to weight loss and metoprolol and propranolol to modest weight gain. Clinicians should consider potential weight gain when selecting antihypertensive medications.

  PublisherOA PDFDOI

• Advancing Air Pollution Exposure Models with Open-Vocabulary Object Detection and Semantic Segmentation of Street-View Images

  Environmental Science & Technology · 2025-09-27

  articleOpen access

  Mobile monitoring campaigns combined with land use regression (LUR) models effectively capture fine-scale spatial variations in urban air pollution. However, traditional predictor variables often fail to capture the nuances of the built environment and undocumented emission sources. To address this, we developed a framework integrating customizable object-level and segmentation-level visual features from street-view images into stepwise regression and random-forest-based LUR models. Using 5.7 million mobile air pollution measurements (2019–2020) and 0.37 million street-view images (2008–2024), we mapped nitrogen dioxide (NO2), black carbon (BC), and ultrafine particles (UFP) across 46,664 road segments in Amsterdam, The Netherlands. Incorporating street-view images improved model performance, increasing R2 by 0.01–0.05 and reducing mean absolute errors by 0.7–10.3%. Sensitivity analyses indicated that key street-view-derived visual features remained stable across years and seasons. Using images from nearby years expanded training instances, thereby enhancing alignment with mobile measurements at fine granularity. Our open-vocabulary object detection module identified influential but previously unrecognized object predictors, such as chimneys, traffic lights, and shops. Combined with segmentation-derived features (e.g., walls, roads, grass), street-view images contributed 8–18% feature importance to model predictions. These findings highlight the potential of visual data in enhancing hyperlocal air pollution mapping and exposure assessment.

  PublisherDOI

• Developing Nationwide Estimates of Built Environment Quality Characteristics Using Street-View Imagery and Computer Vision

  Environmental Science & Technology · 2025-07-03 · 5 citations

  articleOpen access

  Environmental health studies commonly rely on urban composition measures for built environment exposure assessment. However, quality measures are equally important, as they directly influence health behaviors. We leveraged computer vision and street-view imagery to estimate five components of built environment quality (perceived beauty, relaxation potential, nature quality, safe for walking, and safety from crime) across all U.S. cities, explicitly addressing socio-demographic and temporal biases. We collected 72 516 surveys via Amazon Mechanical Turk, where participants ranked street-view images and provided socio-demographic data. Deep learning models predicted quality metrics at 120 million street locations for 2008, 2012, 2016, and 2020. Cross-validation accuracy ranged from 73% (nature quality) to 59% (safety from crime) compared to 50% expected by random chance. Adjusting sampling weights based on demographics reduced but did not eliminate biases for Hispanic/Latino and Native Hawaiian or Pacific Islander groups (3.5 and 4% lower accuracy, respectively). We also adjusted model predictions for seasonal biases, correcting higher scores from late spring and early summer imagery (p < 0.001). The resulting nationwide estimates of street-level beauty, relaxation, nature quality, and safety for walking (but not safety from crime) can inform epidemiological research, urban planning strategies, and public health interventions.

  PublisherDOI

• Birth outcomes in relation to neighborhood food access and individual food insecurity during pregnancy in the Environmental Influences on Child Health Outcomes (ECHO)-wide cohort study

  UNC Libraries · 2025-03-02

  articleOpen access
  PublisherDOI

• Abstract 054: Prospective associations of pregnancy heavy metals and essential elements with women’s mid-life obesity risk: implications of folate supplementation as a possible intervention strategy to mitigate metal-related health effects

  Circulation · 2025-03-11

  article

  Background: Pregnancy is a critical period for women’s long-term cardiometabolic health, with women being particularly sensitive to environmental exposures. The effects of heavy metals and essential elements during pregnancy on long-term obesity risk are understudied. Cohort studies and trials suggest that folate may mitigate metal toxicity—a recent AHA Scientific Statement on metals identified this area of research as a critical gap and priority. Objective: 1) To investigate the associations of pregnancy levels of metals and elements with women’s mid-life obesity risk; and 2) to explore whether adequate pregnancy folate mitigates the obesogenic effects of metals. Methods: Project Viva is a pregnancy cohort enrolled in Eastern MA between 1999-2002 (median age: 32.9y). We measured (As, Ba, Cd, Cs, Hg, Pb) and elements (Cu, Mg, Mn, Se, Zn) in red blood cells and folate in plasma collected during the first trimester. At the Mid-Life visit (2017-2021; median age: 51.2y), we measured weight and height and defined obesity as BMI &gt;30 kg/m 2 (reference: ≤30 kg/m 2 ). We examined associations of metals and elements with obesity using modified Poisson regression, adjusting for confounders ( Figure 1 footnote ). We used Bayesian kernel machine regression (BKMR) to assess the mixture effects of all metals, elements, and folate. Results: We followed 500 women (72% White, 11% Black) for a median of 18.1y (range: 17.5-20.8y). Cs and Cu were associated with a lower risk of obesity: per doubling, Cs and Cu were associated with 0.78 (95% CI: 0.63-0.97) and 0.71 (95% CI: 0.50-0.99) times the obesity risk, respectively. Mg, Se, and Zn were also associated with &gt;10% lower obesity risk, though the 95% CIs crossed the null ( Figure 1 ). BKMR results confirmed consistent dose-response associations ( Figure 2 ). Although neither As nor folate was individually associated with obesity, they showed an interaction in association with obesity ( Figure 3 ): at lower folate levels, As was associated with a higher obesity risk, but as folate levels increased, the As-obesity association was attenuated and eventually became inverse. Conclusion: Optimal pregnancy levels of essential elements (e.g., Cu, Se, Mg, Zn) were associated with a lower risk of mid-life obesity, while adequate folate levels may counteract the obesogenic effects of As. Our study advances a research priority in the AHA Scientific Statement, suggesting folate as a potential intervention strategy to mitigate metal-related health effects.

  PublisherDOI

• Associations of Metal Mixtures During Early Pregnancy With Midlife Obesity and Body Composition: A Prospective Study

  Obesity · 2025-08-26

  articleOpen access

  OBJECTIVE: To examine the prospective associations of metal mixtures during pregnancy with midlife adiposity and explore metal-folate interactions. METHODS: In 500 participants from Project Viva, we measured six non-essential metals (arsenic, barium, cadmium, cesium, mercury, and lead) and five essential metals (copper, magnesium, manganese, selenium, and zinc) in red blood cells and folate in plasma collected during early pregnancy (mean gestational age: 10.0 weeks; mean age: 32.9 years). We assessed midlife (mean age: 51.2 years) adiposity using BMI and dual-energy X-ray absorptiometry (DXA) measures. We used multivariable-adjusted linear and multinomial logistic regression models to analyze individual exposures and Bayesian kernel machine regression to examine exposure mixtures. RESULTS: Higher arsenic, cesium, and mercury levels were associated with lower midlife DXA percentage fat, total fat mass index, and/or trunk fat mass index, even after adjustments for diet in pregnancy. We observed an antagonistic interaction between folate and arsenic: arsenic was associated with higher obesity risk at lower folate levels but lower obesity risk at higher folate levels. The essential metal mixture tended to be associated with lower midlife BMI and obesity risk. CONCLUSIONS: Higher pregnancy levels of arsenic, cesium, mercury, and the mixture of essential metals were associated with lower midlife adiposity.

  PublisherOA PDFDOI

• Long‐Term Medication‐Induced Weight Change Across Common Antiseizure Medications: A Target Trial Emulation Study

  Obesity · 2025-10-05 · 3 citations

  article

  OBJECTIVE: To estimate long-term weight change after initiation and adherence to commonly used antiseizure medications (ASMs) and examine differences in weight change across ASMs compared to topiramate. METHODS: We included 52,309 adult patients who initiated ASMs, applied a target trial emulation approach to control time-varying confounding and selection bias, and examined the long-term comparative effects on weight change after initiating and adhering to different ASMs at 6 and 12 months post initiation. RESULTS: The most commonly initiated ASM was topiramate (41.2%). In comparison to topiramate, we estimated higher 6-month weight change under initiation and adherence to levetiracetam 0.94 kg (95% CI 0.20, 1.64), lamotrigine 1.44 kg (0.74, 1.99), valproate 2.42 kg (1.71, 2.88), carbamazepine 1.32 kg (0.46, 2.16), and oxcarbazepine 1.74 kg (0.85, 2.71), with similar results at 12 months and in sensitivity and subgroup analyses. These results were driven mostly by weight loss with use of topiramate rather than weight gain with use of other ASMs. Results were similar though attenuated when accounting for medication initiation only. CONCLUSIONS: Topiramate was associated with weight loss at 6 and 12 months under either initiation and subsequent adherence or initiation-only effects; other medications were associated with higher weight change. These results provided important information to help with decision-making regarding ASM initiation.

  PublisherDOI

• Associations of Perfluoroalkyl and Polyfluoroalkyl Substances With Cardiovascular Disease Incidence in Adults With Prediabetes: Findings From the Diabetes Prevention Program

  Journal of the American Heart Association · 2025-12-19

  articleOpen access1st authorCorresponding

  Background Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are persistent, widespread environmental contaminants linked to cardiometabolic outcomes including obesity, hyperlipidemia, and diabetes. We examined whether baseline plasma PFAS concentrations are associated with incident cardiovascular disease (CVD) in adults with prediabetes, leveraging data from DPPOS (Diabetes Prevention Program Outcomes Study). Methods Among 1382 participants, we quantified baseline plasma concentrations of 6 PFAS. We used Cox proportional hazards models to estimate the risks of developing CVD outcomes during a median of 21 years of follow‐up for each PFAS and used quantile g‐computation to evaluate the joint effect of all 6 PFAS. Effect modification by age, sex, menopausal status, diet, and physical activity was explored. Results The incidence of major adverse cardiovascular events was 9.6%; 3.9% had CVD‐related death. Each increase in interquartile range (1.1 ng/mL) in 2‐( N ‐methyl‐perfluorooctane sulfonamido) acetate was associated with a 16% higher risk of major adverse cardiovascular events (95% CI, 1–33%) and a 24% higher risk of CVD death (95% CI, 2–52%). Higher concentrations of perfluorohexane sulfonate, perfluorooctane sulfonate, 2‐( N ‐ethyl‐perfluorooctane sulfonamido) acetate, and perfluorooctanoate were associated with greater risk of CVD outcomes, including nonfatal myocardial infarction, hospitalized congestive heart failure, and cardiovascular death. However, PFAS mixture was not associated with CVD. Age, sex, treatment arm, physical activity, and diet did not modify the associations of individual PFAS. Conclusion In adults with prediabetes, higher plasma concentrations of select PFAS, but not their mixture, were prospectively associated with increased CVD risk. These findings underscore PFAS as a potential environmental risk factor for CVD in high‐risk populations. REGISTRATION: URL: https://clinicaltrials.gov/ ; Unique identifiers: NCT00004992 and NCT00038727.

  PublisherDOI

• GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women

  International Journal of Behavioral Nutrition and Physical Activity · 2025-07-06 · 4 citations

  articleOpen access

  BACKGROUND: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and day-to-day dynamic exposures, potentially misclassifying greenspace and limiting policy relevance. METHODS: We analyzed data from the US-based Nurses' Health Study 3 Mobile Health Substudy (2018-2020). Participants wore Fitbits™ and provided smartphone global positioning system (GPS) for four 7-day periods throughout the year. Street-view greenspace (%trees, %grass, %other greenspace [flowers/plants/fields]) were derived from 2019 street-view imagery using deep-learning algorithms at a 100-meter resolution and linked to 10-minute GPS observations. Average steps-per-minute for were calculated for each 10-minute period following each GPS observation. Generalized Additive Mixed Models examined associations of street-view greenspace exposure with PA, adjusting for individual and area-level covariates. We considered effect modification by region, season, neighborhood walkability and socioeconomic status (SES), temperature, and precipitation. RESULTS: = 39.4 years, n = 304,394 observations). Mean steps-per-minute per 10-minutes were 6.9 (SD = 14.6). An IQR increase (18.7%) in street-view trees was associated with a 0.36 steps-per-minute decrease (95%CI: -0.71, -0.01). In addition, an IQR increase (10.6%) in grass exposure was associated with a 0.59 steps-per-minute decrease (95% CI: -0.79, -0.40); however, the association was non-linear and flattened out after the 75th percentile of street-view grass. Conversely, an IQR increase (1.2%) in other greenspace was associated with a 1.99 steps-per-minute increase (95%CI: 0.01, 3.97). Associations were stronger in the spring and in higher SES neighborhoods, and among residents of the Northeast. CONCLUSIONS: In this prospective cohort, momentary street-view exposure to trees and grass was inversely associated with PA, while exposure to other greenspace was positively associated. Future research should confirm these results in other populations and explore the mechanisms through which specific greenspace components influence PA.

  PublisherOA PDFDOI

Frequent coauthors

• Marie‐France Hivert

  Harvard Pilgrim Health Care

  166 shared

• Emily Oken

  150 shared

• Sheryl L. Rifas–Shiman

  Harvard University

  138 shared

• Andrés Cárdenas

  Stanford University

  97 shared

• Diane R. Gold

  Harvard University

  66 shared

• Izzuddin M. Aris

  Harvard Pilgrim Health Care

  62 shared

• Abby F. Fleisch

  Maine Medical Center

  59 shared

• Antonia M. Calafat

  Centers for Disease Control and Prevention

  44 shared

Education

• ScD, Environmental Health

  Harvard T.H. Chan School of Public Health

• M.S, Public Health

  Kaohsiung Medical University

  2013

• B.S, Genetic, Cell Biology and Development

  University of Minnesota Twin Cities

  2006