Current Research Projects
Beijing Household Energy Transitions (BHET):
(with Jill Baumgartner)
Air pollution is a leading public health problem. Over 400 million Chinese homes burn coal to meet their indoor space heating needs, leading to high levels of air pollution and health impacts in adults and children. Coal burning in China also contributes to poor air quality and mercury contamination in Canada. This project will assess how transitioning away from coal and introducing new clean heating technology in China will impact the health and environment of people who live in homes impacted by policy changes.
Funding: Canadian Institutes for Health Research
Tabora Maternal and Newborn Health Initiative (TAMANI):
(with Arijit Nandi, Ifakara Health Institute, CARE Canada)
We are monitoring and evaluating a health systems strengthening program being implemented by CARE Canada, in partnership with the Society of Obstetricians and Gynaecologists of Canada (SOGC) and the Canadian Society for International Health (CSIH), in the Tabora region of Tanzania. The aim of this program is to reduce maternal and newborn mortality and morbidity by improving the availability of quality maternal and newborn healthcare services. Activities include: training and mentoring of Regional and District Council Health Management Teams (R/CHMTs) in data management and usage, supply chain management, budgeting and leadership; development of an emergency transportation system; refurbishing health centre and hospital maternity wards and procuring Basic Emergency Obstetric and Newborn CARE (BEmONC) and Comprehensive Emergency Obstetric and Newborn CARE (CEmONC) equipment; training and mentoring of health care workers (HCWs) on BEmONC, CEmONC and family planning; and training and support of Community Health Workers (CHWs) to deliver quality maternal and newborn health education and promote utilization of health care services. We will be assessing the program’s impacts by integrating monitoring and evaluation with the delivery of interventions using a randomized phase-in or “stepped wedge” design.
Funding: Global Affairs Canada
Affordable daycare to empower indian women
(with Arijit Nandi)
There are structural barriers to women’s empowerment in India. Among these barriers is the lack of affordable and reliable day-care services. The responsibility of providing childcare is imposed primarily on women and contributes to gender inequalities experienced by women over the life-course. The provision of affordable and reliable day-care services is a potentially important policy lever for empowering Indian women. Access to day-care might reduce barriers to labor force entry and generate economic opportunities for women. However, empirical evidence concerning the effects of day-care programs in low-and-middle-income countries is scarce. We propose a cluster-randomized impact evaluation for estimating the effect of a community-based day-care program on empowerment, economic opportunity, and health among mothers living in rural Rajasthan, India. This interdisciplinary research initiative will address an important research gap and has the potential to inform policies for improving the day-care system in India in ways that promote inclusive economic growth.
The video below provides some additional details about the project and some essential context for where this work is being done.
Funding: International Development Research Centre
Using Natural Experiments to Evaluate the Impact of Population Health Interventions on Health Inequality
(with Erin Strumpf and Jay Kaufman)
A wide range of public health policies and population health interventions have been implemented with the goal of improving population health. The extent to which the causal effects of these policies have been measured is uneven, and little to no attention has been paid to their effects on vulnerable population groups. These interventions and policies are likely to affect individuals of different socioeconomic status differently, thereby reducing or magnifying existing differences in health behaviours and health outcomes. This project, funded by the Canadian Institutes for Health Research, will apply innovative analytic methods to measure the causal impacts of several population health interventions on health inequalities.
Impact Of Reproductive Health Restrictions On Women’s Health Outcomes
(with Nichole Austin and Erin Strumpf)
Abortion rates have been steadily decreasing in both Canada and the US, but the cause remains poorly understood. In the US, where reproductive health policies vary considerably from state to state, abortion opponents credit a recent upsurge in state-level abortion restrictions (including mandatory waiting periods, mandatory counseling, and provider licensing requirements), while advocates argue that the decline is due to empowering initiatives, such as improved access to contraception and sex education programs. Existing research, particularly on restrictions, is largely descriptive; this prevents us from understanding the causal effects of, and potentially complex interplay between, restrictive and empowering policies on abortion rates. Disentangling the effects of these factors is challenging but important, as these policies likely have a marked effect on population health. This project will bridge this knowledge gap by deconstructing the recent decline in US abortion rates and teasing apart the causal impact of empowering and restrictive initiatives. The substantial state-to-state variation in the timing of policy implementation in the US will permit the use of quasi-experimental study study designs to minimize confounding. Abortion is a common and safe medical procedure, but abortion policy decisions are currently being made with low quality evidence on effectiveness or long-term health implications. This work will ultimately provide a better understanding of why abortion rates are declining, which is vital in informing future policy decisions.
Funding: Fonds de recherche du Québec – Santé (FRQS)
Past RESEARCH PROJECTS
Measuring Health Inequalities
The general objective of this project, funded by the Canadian Institutes for Health Research, is to identify the role of value judgments in the generation, presentation, and interpretation of health inequalities information. More specifically, the aims of this project are:
- To investigate and describe how the use of particular inequality measures may implicitly embed value judgments in data, through an empirical analysis of published health inequalities research.
- To investigate how individuals’ moral evaluations of health inequalities may be influenced by contextual factors in the presentation of data through controlled experimental research.
For more information, see the project website.
Modelling the Effects of Interventions on Health Inequalities
The Simulation Technology for Applied Research (STAR) team brings together university and government scientists, policymakers and administrators interested in the application of computer simulation technology to the assessment of health interventions and policies. Funded by a New Emerging Team (NET) grant from the Canadian Institute of Health Research (CIHR), this research program responds to the growing need for comprehensive information and tools to assist policymakers in making informed choices about investments in health care, treatments, as well as public and population health initiatives with the goal of improving system-level decision making and ultimately, population health.
Effects of Self-Report Bias on Between- and Within-Country Health Inequalities in Disabilities
(with Spencer Moore and Seungmi Yang)
As people in many countries are living longer, health conditions that are not usually fatal, such as mental disorders, arthritis, and vision and hearing problems are becoming increasingly important aspects of health and well-being. We often measure these aspects of health by asking people to report on how much difficulty they have with certain activities or health conditions. However, people from different countries or from different backgrounds may interpret the same question differently. For example, asking a 25-year old and a 70-year old how much difficulty they have walking stairs may be difficult if the two individuals use different scales when thinking about their ability. This means that observed differences between countries or social groups reflect both objective differences in health and also differences in the way people interpret the questions. Recent developments in survey techniques now allow the possibility of accounting for differences in the way individuals understand questions about their health by using brief descriptions of specific health states to put everyone’s responses on a similar scale. This study will use these ‘anchors’ to provide better measures of the prevalence of non-fatal health conditions across different countries, and between gender and economic groups within countries. The findings from this study will help to provide better measures of the importance of non-fatal health conditions across the globe.
Nandi A, Harper S. How consequential is social epidemiology? A review of recent evidence. Current Epidemiology Reports 2014. doi: 10.1007/s40471-014-0031-3
Frenz P, Delgado I, Kaufman JS, Harper S. Achieving effective universal health coverage with equity: evidence from Chile. Health Policy Plan. 2014;29(6):717-731.
Harper S, MacLehose RF, Kaufman JS. Trends in the black-white life expectancy gap among US states, 1990-2011. Health Affairs 2014;33(8):1375-82.
Harper S, King N, Meersman SC, Breen N, Reichman ME, Lynch J. Juicios de valor implícitos en la medición de las desigualdades en salud* Revista Panamericana de Salud Pública 2014;35(4):293-304. [Spanish translation of Harper S, et al. Milbank Quarterly 2010;88:4-29.]
Auger N, Feuillet P, Martel S, Lo E, Barry AD, Harper S. Mortality inequality in populations with equal life expectancy: Arriaga's decomposition method in SAS, Stata, and Excel. Annals of Epidemiology. 2014;24(8):575-580.e571.
Manuel DG, Ho TH, Harper S, Anderson GM, Lynch J, Rosella LC. Modelling preventive effectiveness to estimate the equity tipping point: At what coverage can individual preventive interventions reduce socioeconomic disparities in diabetes risk? Chronic diseases and injuries in Canada. 2014;34(2-3):94-102.
King NB, Fraser V, Boikos C, Richardson R, Harper S. Determinants of increased opioid-related mortality in the united states and canada, 1990-2013: A systematic review. Am J Public Health. 2014;104(8):e32-e42.
McKinnon B, Harper S, Kaufman JS, Abdullah M. Distance to emergency obstetric services and early neonatal mortality in ethiopia. Tropical Medicine and International Health. 2014;19(7):780-90.
Hutcheon JA, Harper S, Strumpf EC, Lee L, Marquette G. Using inter-institutional practice variation to understand the risks and benefits of routine labour induction at 41+0 weeks. BJOG: An International Journal of Obstetrics and Gynaecology. 2014. doi: 10.1111/1471-0528.13007. [Epub ahead of print]
McKinnon B, Harper S, Kaufman JS, Bergevin Y. Progress in reducing socioeconomic inequalities in neonatal mortality in low- and middle-income countries: a multi-country analysis. Lancet Global Health 2014;2(3):e165-e173. [pdf]
Smith BT, Smith PM, Harper S, Manuel DG, Mustard CA. Reducing Social Inequalities in Health: The Role of Simulation Modeling in Evaluating the Impact of Population Health Interventions. J Epidemiol Community Health 2014;68(4):384-9. doi: 10.1136/jech-2013-202756. [pdf]
Harper S, Strumpf EC, Burris S, Davey Smith G, Lynch J. The Effect of Mandatory Seat Belt Laws on Seat Belt Use by Socioeconomic Position. Journal of Policy Analysis and Management (in press). [pdf]
Kaufman JS, Harper S. Health equity: Utopian and scientific. Preventive Medicine 2013;57:739–40. [pdf]
Nandi A, Charters TJ, Strumpf EC, Heymann J, Harper S. Economic conditions and health behaviours during the 'Great Recession'. J Epidemiol Community Health. 2013;67:1038-1046. [pdf]
Maika M, Mittinty MN, Brinkman S, Harper S, Satriawan E, Lynch JW. Changes in Socioeconomic Inequality in Indonesian Children's Cognitive Function from 2000 to 2007: A Decomposition Analysis. PLoS ONE 2013; 8(10): e78809. doi:10.1371/journal.pone.0078809. [pdf]
Speybroeck N, Carine Van Malderen C, Harper S, Müller B, Devleesschauwer B. Simulation models for socioeconomic inequalities of health: A systematic review. Int J Environ Res Public Health. 2013; 10(11), 5750-5780. doi:10.3390/ijerph10115750 [pdf]
Harper S, Ruder E, Roman HA, Geggel A, Nweke O, Payne-Sturges D, Levy JI. Using inequality measures to incorporate environmental justice into regulatory analyses. Int J Environ Res Public Health. 2013;10(9):4039-59. doi: 10.3390/ijerph10094039. [pdf]
Auger N, Harper S, Barry AD, Diverging socioeconomic inequality in life expectancy of Francophones and Anglophones in Montréal, Québec: Tobacco to blame? Journal of Public Health. 2013;21(4):317-324. [pdf]
McKinnon B, Harper S, Moore S. The relationship of living arrangements and depressive symptoms among older adults in sub-Saharan Africa. BMC Public Health 2013;13;682. doi: 10.1186/1471-2458-13-682.
Harper S, King NB, Young ME. Impact of selective evidence presentation on judgments of health inequality trends: an experimental study PLoS ONE 2013;8(5): doi: 10.1371/journal.pone.0063362. [pdf]
Harper S, King N. Best practice for what? The Milbank Quarterly. 2013;91(1):205-209. [pdf]
Platt R. Harper S. Survey data with sampling weights: is there a "best" approach? Environmental Research 2013;120:43-144. [pdf]
King NB, Harper S, Young ME. Who cares about health inequalities? Health Policy & Planning 2013;28(5):558-571. [pdf]
Young ME, King NB, Harper S. The influence of popular media on perceptions of personal and population risk in possible disease outbreaks. Health, Risk, and Society 2013;15(1):103-114. [pdf]
Auger N, Park AL, Harper S. Francophone and Anglophone perinatal health: temporal and regional inequalities in a Canadian setting, 1981-2008. International Journal of Public Health 2012;57(6):925-934.
Speybroeck N, Harper S, de Savigny D, Victora C. Inequalities of health indicators for policy makers: Seven Hints. Int J Public Health 2012;57(5): 855-858. [Erratum published: 2012;57(5): 859-860].
Kaufman JS, Harper S. Deficiency of the odds ratio for common outcomes [Letter]. Am J Psychiatry. 2012 Oct;169(10):1118; author reply 1118-9. [Comment on: Chen LS et al. Interplay of genetic risk factors (CHRNA5-CHRNA3-CHRNB4) and cessation treatments in smoking cessation success. Am J Psychiatry 2012; 169:735–742.]
Harper S, Strumpf EC. Social epidemiology: Questionable answers and answerable questions. Epidemiology 2012;23(6):795-8.
Hosseinpoor AR, Bergen N, Kunst A, Harper S, Guthold R, Rekve D, Tursan d'Espaignet E, Naidoo N, Chatterji S. Socioeconomic inequalities in risk factors for noncommunicable diseases in low-income and middle-income countries. BMC Public Health. 2012 Oct 28;12(1):912.
King NB, Harper S, Young ME. Use of relative and absolute effect measures in reporting health inequalities: structured review. BMJ 2012;345:e5774.
Elani HW, Harper S, Allison PJ, Bedos C, Kaufman JS. Socio-economic Inequalities and Oral Health in Canada and the United States. Journal of Dental Research 2012;91(9):865–870.
Hosseinpoor AR, Harper S, Lee J, Lynch J, Mathers C, Abou-Zahr C. International shortfall inequality in life expectancy in women and in men, 1950-2010. Bulletin of the World Health Organization 2012;90:588-594.
Hosseinpoor AR, Bergen N, Mendis S, Harper S, Verdes E, Kunst A, Chatterji S. Socioeconomic inequality in the prevalence of noncommunicable diseases in low- and middle-income countries: Results from the World Health Survey. BMC Public Health 2012;12:474.
Yang S, Khang Y-H, Harper S, Lynch J, Chun H. The Changing Gender Differences in Life Expectancy in Korea 1970-2005. Social Science & Medicine 2012;75:1280-7.
Toporowski A, Harper S, Fuhrer R, Buffler PA, Detels R, Krieger N, Franco EL. Burden of disease, health indicators and challenges for epidemiology in North America. Int J Epidemiol. 2012;41(2):540-56.
Harper S, Rushani D, Kaufman JS. Trends in the Black-White Life Expectancy Gap, 2003-2008. JAMA 2012; 307: 2257-2259.[pdf]
Banack HR, Harper S, Kaufman JS. Re: Number of coronary heart disease risk factors and mortality in patients with myocardial infarction [Letter]. JAMA 2012;307:1137-8. [Comment on: Canto JG, Kiefe CI, Rogers WJ, et al. Number of coronary heart disease risk factors and mortality in patients with first myocardial infarction. JAMA. 2011;306(19):2120–2127.]
Auger N, Harper S, Barry AD, Trempe N, Daniel M. Inequality in life expectancy between the Francophone majority and Anglophone minority of a Canadian population. European J Epidemiol 2012;27:27–38.[pdf]
Harper S, Strumpf EC, Kaufman JS. Do Medical Marijuana Laws Increase Marijuana Use? Replication Study and Extension. Ann Epidemiol 2012;22:207-12.[pdf]
Harper S, Kaufman JS, King NB. Re: Cigarette smoking as a risk factor for coronary heart disease in women compared with men: a systematic review and meta-analysis of prospective cohort studies. [Letter] Lancet 2012;379:801-2. [Comment on: Huxley RR, Woodward M. Cigarette smoking as a risk factor for coronary heart disease in women compared with men: a systematic review and meta-analysis of prospective cohort studies. Lancet. 2011 Oct 8;378(9799):1297-305]
Auger N, Delézire P, Harper S, Platt RW. Maternal education and stillbirth. Epidemiology 2012;23: 247–254.[pdf]
Auger N, Park AL, Harper S, Daniel M, Roncarlo F, Platt RW. Educational inequalities in preterm and term small-for-gestational-age birth over time. Ann Epidemiol 2012;22:160-67.[pdf]
Harper S, McKinnon B. Global socioeconomic inequalities in tobacco use: Internationally comparable estimates from the World Health Surveys. Cancer Causes Control 2012;23:11–25.[pdf]
Kaufman, J.S., Harper, S. & King, N.B. A more complete picture of higher cardiovascular disease prevalence among blacks compared to whites. Am J Med 124, e5–6; reply e7 (2011).[pdf]
Agha G, Murabito JM, Lynch JW, Abrahamowicz M, Harper SB, Loucks EB. Relation of Socioeconomic Position with Ankle-Brachial Index. Am J Cardiology 2011;108:1651-7.[pdf]
Auger N, Roncarlo F, Harper S. Increasing educational inequality in preterm birth in Québec, Canada, 1981-2006. Journal of Epidemiology & Community Health 2011;65:1091-1096.[pdf]
Auger N, Gamache P, Adam-Smith J, Harper S. Relative and absolute disparities in preterm birth related to neighbourhood education. Ann Epidemiol 2011;21;481-488.[pdf]
Sadana R. Harper S. Data systems linking social determinants of health with health outcomes - advancing public goods to support research and evidence-based policy and programs. Public Health Reports 2011;126 Suppl 3:6-13.[pdf]
Larose A, Moore S, Harper S, Lynch J. Global income-related inequalities in HIV testing. J Public Health 2011;33:345-352.[pdf]
Adam-Smith J, Harper S, Auger N. Causes of widening life expectancy inequalities in Québec, Canada, 1989-2004. Can J Public Health 2011;102:375-381.[pdf]
Smith BT, Loucks EB, Harper S, Abrahamowicz M, Fox CS, Lynch JW. Life course socioeconomic position and incidence of type 2 diabetes: Framingham Offspring Study. Am J Epidemiol 2011;173(4):438-447.[pdf]
McKinnon B, Harper S, Moore DS. Decomposing Income Related Inequality in Cervical Screening in 67 Countries. Int J Public Health 2011;56(2):139-152.[pdf] *Editor's choice article
Harper S, Lynch J, Davey Smith G. Social determinants and the decline of cardiovascular diseases: Understanding the links. Ann Rev Public Health 2011;32:39-69.[pdf]
Speybroeck N, Konings P, Lynch J, Harper S, Hosseinpoor A, Berkvens D, Lorant V, Geckova A. Decomposing socioeconomic health inequalities. Int J Public Health 2010;55:347-51.[pdf]
McTavish S, Moore S, Harper S, Lynch J. National female literacy, individual socio-economic status, and maternal health care use in sub-Saharan Africa. Soc Sci Med 2010;71(11): 1958-63.[pdf]
Kopec JA, Philippe Finès P, Manuel DG, Buckeridge D, Flanagan WM, Oderkirk J, Abrahamowicz M, Harper S, Sharif B, Okhmatovskaia A, Sayre EC, Rahman MM, Wolfson MC. Validation of Population-Based Disease Simulation Models: A Review of Concepts and Methods. BMC Public Health 2010;10:710.[pdf]
Harper S. Inequalities in Cancer Survival and the NHS Cancer Plan: Evidence of Progress? Br J Cancer 2010;103:437-8.[pdf]
King NB, Kaufman JS, Harper S. Relative measures alone tell only part of the story. Am J Public Health (letter) 2010;100:2014-2015.[pdf]
Yang S, Khang Y-H, Harper S, Davey Smith G, Leon D, Lynch J. Understanding the Rapid Increase in Life Expectancy in South Korea. Am J Public Health 2010;100:896-903.[pdf]
Moore S, Hall JN, Harper S, Lynch JW. Global and National Socio-Economic Disparities in Obesity, Overweight, and Underweight Status. Journal of Obesity 2010;2010:1-11.[pdf]
Konings P, Harper S, Lynch J, Berkvens D, Hosseinpoor A, Lorant V, Geckova A, Speybroeck N. Analysis of Socioeconomic Inequalities using the Concentration Index. Int J Public Health 2010;55:71-74.[pdf]
Harper S, King NB, Meersman SC, Reichman ME, Breen N, Lynch J. Implicit Value Judgements in the Measurement of Health Inequalities. Milbank Quarterly 2010;88:4-29.[pdf]
Harper S. Essay Review: Rose’s Strategy of Preventive Medicine. Int J Epidemiol 2009;38:1743-45.[pdf]
Harper S. Commentary: Trends in indigenous inequalities in health in New Zealand. Int J Epidemiol 2009;38: 1722-1724.[pdf]
Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman ME. Trends in race-ethnic and socioeconomic disparities in breast cancer incidence, stage at diagnosis, screening, mortality, and survival, 1987-2005. Cancer Epidemiol Biomarkers Prev 2009;18:121-31.[pdf]
Hall JN, Moore DS, Harper S, Lynch J. Global variability in low fruit and vegetable consumption. Am J Prev Med 2009; 36(5):402-409.[pdf]
Khang Y-H, Lynch J, Yang S, Harper S, Yun S-C, Jung-Choi K, Kim HR. The contribution of material, psychosocial, and behavioral factors in explaining educational and occupational mortality inequalities in a nationally representative sample of South Koreans: Relative and absolute perspectives. Soc Sci Med 2009;68(5):858-66.[pdf]
Alvarado BE, Harper S, Platt R, Davey Smith G, Lynch G. Would Achieving Healthy-People 2010’s Targets Reduce Both Population Levels and Social Disparities in Heart Disease? Circ Cardiovasc Qual Outcomes 2009;2:598-606.[pdf]
Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman ME. An overview of methods for monitoring social disparities in cancer with an example using trends in lung cancer incidence by socioeconomic position and race-ethnicity, 1992-2004. Am J Epidemiol 2008;167(8):889-99.[pdf]
Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman ME. Response to Messer. Am J Epidemiol 2008;167(8):905-7.
Harper S, Lynch J. Trends in socioeconomic inequalities in adult health behaviors among U.S. states, 1990-2004Public Health Rep 2007;122(2):177-89.[pdf]
Harper S, Lynch J. Highly active antiretroviral therapy and socioeconomic inequalities in AIDS mortality in Spain. (letter) Eur J Public Health 2007;17(2):231.
Harper S, Lynch J, Burris S, Davey Smith G. Trends in the black-white life expectancy gap in the United States, 1983-2003. JAMA 2007;297(11):1224-32.[pdf]
Cho H-J, Khang Y-H, Yang S, Harper S, Lynch J. Socioeconomic differentials in cause-specific mortality among South Korean adolescents. Int J Epidemiol 2007; 36:50-57.[pdf]
Harper S. Did clean water reduce black-white mortality inequalities in the United States? Int J Epidemiol 2007;36: 248-257.[pdf]
Harper S, Lynch J. Commentary: Using innovative inequality measures in epidemiology. Int J Epidemiol 2007;36: 926-928.[pdf]
Lynch J, Davey Smith G, Harper S, Bainbridge K. Explaining the social gradient in coronary heart disease: comparing relative and absolute risk approaches. J Epidemiol Community Health 2006;60:436-441.[pdf]
Jackson R, Lynch J, Harper S. Does Rose’s population prevention axiom apply to coronary heart disease prevention in the 21st century? BMJ 2006;332:617-618.
Kelleher C, Lynch JW, Daly L, Harper S, Fitz-simon N, Bimpeh Y, Daly E, Ulmer H. The ‘Americanisation’ of migrants: Evidence for the contribution of ethnicity, social deprivation, lifestyle and life-course processes to the mid-20th century coronary heart disease epidemic in the US. Soc Sci Med 2006;63:465-84.
Harper S. What explains widening geographic differences in life expectancy in New Zealand? Int J Epidemiol 2006;35:604-6.[pdf]
Lynch J, Harper S, Davey Smith G, Kaplan G. Association between income inequality and mortality across U.S. states depends upon time period and source of income data. Am J Public Health 2005;95:1424-1430.
Huynh M, Parker J, Pamuk E, Harper S, Schoendorf K. Contextual effect of income inequality on birth outcomes. Int J Epidemiol 2005;34: 888-895.
Lynch J, Davey Smith G, Harper S, Hillemeier M, Ross N, Wolfson M. Is income inequality a determinant of population health? Part 1. A systematic review. Milbank Q 2004;82(1):5-99.[pdf]
Lynch J, Davey Smith G, Harper S, Hillemeier M. Is income inequality a determinant of population health? Part 2. U.S. national and regional trends in income inequality and age- and cause-specific mortality. Milbank Q 2004;82(2):355-400.[pdf]
Lynch J, Harper S, Davey Smith G, Ross N, Wolfson M, Dunn J. US regional and national cause-specific mortality and trends in income inequality: descriptive findings. Demographic Res [serial online] 2004;Special collection 2(Article 8):184-228. Available at http://www.demographic-research.org/special/2/8/s2-8.pdf.
Kelleher CC, Lynch JW, Harper S, Tay J, Nolan G. Hurling Alone? How social capital failed to save the Irish from cardio-vascular disease in the United States of America. Am J Public Health 2004;94:2162-9.
Hillemeier MM, Lynch J, Harper S, Raghunathan T, Kaplan GA. Relative or absolute standards for child poverty: a state-level analysis of infant and child mortality. Am J Public Health 2003; 93(4):652-7.
Hillemeier MM, Lynch J, Harper S, Casper M. Measuring contextual characteristics for community health. Health Serv Res 2003;38:1645-1718.
Lynch, J, Harper S, and Davey Smith G. Commentary: Plugging leaks and repelling boarders—where to next for the SS Income Inequality? Int J Epidemiol 2003;32(6):1029-36.[pdf]
Harper S, Lynch, J, Hsu, WL, Everson, SA, Hillemeier MM, Raghunathan TE, Salonen JT, Kaplan GA. Life course socioeconomic conditions and adult psychosocial functioning. Int J Epidemiol 2002;31(2):395-403.
Book Chapters, Reviews, and Reports
Harper S, Lynch J. Assessment of Various Measures of Health Disparities Using Databases Containing Data Relevant to Healthy People 2010 Cancer Related Goals. National Cancer Institute, 2007.[pdf]
Harper S, Lynch J. Methods for Measuring Cancer Disparities: A Review Using Data Relevant to Healthy People 2010 Cancer-Related Objectives. National Cancer Institute, 2006.[pdf]
Harper S, Lynch J. Measuring Health inequalities. In: Oakes JM, Kaufman JS (eds.). Methods in Social Epidemiology. New York: Wiley, 2006, pp. 134-68.
Hillemeier MM, Lynch J, Harper S, Casper M. Data Set Directory of Social Determinants of Health at the Local Level. Atlanta, GA: US Department of Health and Human Services, 2004.
Eberhardt MS, Ingram DD, Makuc DM, Pamuk ER, Fried VM, Harper SB, Schoenborn CA, Xia H. Urban and Rural Health Chartbook. Health, United States, 2001. Hyattsville, MD: National Center for Health Statistics, 2001.
McKeown RE, Harper, SB. Epidemiology Kept Simple, by B. Burt Gerstman. Epimonitor 1999;20(6):11-2.
Harper S, Strumpf EC, Kaufman J. Do Medical Marijuana Laws Increase Marijuana Use? Replication Study and Extension. Forthcoming in Annals of Epidemiology. January, 2012 [pdf]
Harper S, Strumpf EC, Burris S, Davey Smith G, Lynch J. Do Mandatory Seat Belt Laws Affect Socioeconomic Inequalities in Seat Belt Use? (July 30, 2012). Available at SSRN: http://ssrn.com/abstract=2120120 [pdf]
Application of Natural Experiments to Evaluate and Answer Social and Development Questions. Institute for Financial Management and Research, Chennai, India, 2016 (joint work with Arijit Nandi) [slides]
Affordable Daycare to Empower Indian Women: Preliminary Baseline Findings. Canadian Economics Association Annual Meeting. Ottawa, Canada, 2016 [slides]
Capitalizing on natural experiments to understand health impacts of policies. Reimagining Health In Cities: New Directions in Urban Health Research, Drexel University, 10 Sep 2015. [slides][video]
Are Tobacco Taxes Increasing Smoking Inequalities? Recent Evidence From Canada. Society for Epidemiologic Research Annual Meeting, Denver, CO 2015. [poster]
Biodemography, Health, and Mortality. Invited Discussant at Population Association of America Annual Meeting. San Diego, 2 May 2015. [slides]
Does seatbelt use explain socioeconomic differences in traffic accident mortality? Poster presentation at Society for Epidemiologic Research Annual Meeting, Seattle, WA, 2014. [poster]
The Impact of Framing the Scale of Inequality on Judgments about Intervention Impacts. “Health Equity: What People Think” Dalhousie 9 Oct 2013. [slides]
Trends and demographic patterns in non-medical use of prescription opioids, 2002-2010. Society for Epidemiologic Research Annual Meeting, June 18-21, 2013, Boston, MA, USA. [slides]
The Effect of Recessions on Suicide Mortality in the United States. Society for Epidemiologic Research Annual Meeting, June 18-21, 2013, Boston, MA, USA. [slides]
The Black-White Life Expectancy Gap: An Update. 25th Annual Walter Booker Memorial Symposium, Los Angeles, CA, 2012 [slides]
Who Cares about Health Inequalities? Society for Epidemiologic Research, Seattle, WA, 2010 [slides]
How Reliable are Self-Reports of Disability? McGill University Health Centre, Montreal, 2010 [slides]
Methods for Assessing Disproportionality. EPA Symposium on Strengthening Environmental Justice, Washington, DC, 2010 [slides]
Global Inequalities in Tobacco Consumption. Robert Wood Johnson Seminar, University of Michigan, 2009 [slides]
Global Inequalities in Life Expectancy. International Union for the Scientific Study of Population Conference, Marrakech, 2009 [slides]
Monitoring Social Inequalities in Health: Integrating Measurement and Value Judgments. Pan-American Health Organization, Washington, DC, 2008 [slides]
Is There a Suicide Belt in the United States? Society for Epidemiologic Research, Chicago, IL, 2008 [slides]
Do Mandatory Seat Belt Laws Reduce Socioeconomic Inequalities in Seat Belt Use? Society for Epidemiologic Research, Boston, MA, 2007 [slides]
Measuring Health Disparities. National Cancer Institute Health Disparities Research Training Symposium, Washington, DC, 2006 [slides]
Accounting for Changes in Social Inequalities in Smoking and Obesity, 1960-2000. Population Association of America, Los Angeles, 2006 [slides]
Why has the Black-White Life Expectancy Gap Recently Declined? Population Association of America, Los Angeles, 2006 [slides]
Datasets and Replication Files
Replication is a hallmark of the scientific enterprise. I strongly support reproducible science and efforts to increase the degree of transparency in the conduct and reporting of scientific studies. Below I provide links to my (evolving) page on the Open Science Framework and to replication datasets for recent papers, posted on Harvard's Dataverse Network.
Monitoring Health Inequalities
Health Disparities Calculator
[Latest Release: Version 1.2.4 - October 29, 2013]
Developed in collaboration with the US National Cancer Institute, the Health Disparities Calculator (HD*Calc) is free statistical software designed to generate multiple summary measures to evaluate and monitor health disparities (HD). HD*Calc was created as an extension of SEER*Stat that allows the user to import SEER data and other population based health data to calculate any of eight disparity measurements.
Several of the measures included in HD*Calc are not commonly used to evaluate cancer-related health disparities. An important function of HD*Calc is to facilitate use of a range of HD measures so that researchers can explore their utility in different situations.
Cross sectional and trend data (e.g., cancer rates, survival, stage at diagnosis) categorized by disparity groups (e.g., area-socioeconomic status, race/ethnicity, geographic areas) can be used with HD*Calc to generate four absolute and seven relative summary measures of disparity. The results are displayed as tables and charts, which may be exported for use in other applications.
Download the software and view tutorials at: http://seer.cancer.gov/hdcalc/index.html
Decomposition of Health Inequalities
Decomp: An R-package to facilitate understanding health inequalities (via Peter Konings and Niko Speybroeck). This statistical package for the free software R enables the quantification of the contributions of determinants to socioeconomic inequality in health. You can find a short tutorial paper on how to use it here.
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I am an associate professor in the Department of Epidemiology, Biostatistics & Occupational Health at McGill University. I am also a member of the McGill University Centre on Population Dynamics and the Montreal Health Equity Research Consortium.
My research focuses on understanding population health and its social distribution, with specific interests in impact evaluation, measuring health inequalities, global health, demography, cancer epidemiology, causal inference, and ethical issues in public health.
More information on specific projects, papers, students, and teaching are in my CV [PDF]
Department of Epidemiology, Biostatistics & Occupational Health, McGill University
1020 Pine Avenue West, Room 34B
Montreal, QC H3A 1A2 CANADA
sam [dot] harper [at] mcgill [dot] ca