ArticleInternational journal for equity in health2021
Leveraging open data to reconstruct the Singapore Housing Index and other building-level markers of socioeconomic status for health services research.
Article in International journal for equity in health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Data Resource Profile: The National Dental Centre Singapore Oral Disease Registry (NDCS-ODR).International journal of epidemiology · 2026Article
- Uncertainty and unmet needs in older high-risk blunt trauma survivors and their caregivers: a multi-centre mixed methods study.Scientific reports · 2026Article
- Prevalence and determinants of ageism experiences in the Singapore population: insights from the HEalthy LOngevity (HELO) survey.GeroScience · 2026Article
- Establishment of a large-scale oral disease registry (NDCS-ODR) in a national specialty center.PloS one · 2026Article
- Singapore Housing Index and prevalence of serious bacterial infections among febrile infants.Frontiers in pediatrics · 2026Article
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- Self-reported temporomandibular disorder pain in a multi-ethnic, Southeast Asian population: prevalence and health impact.BMC oral health · 2025Article
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- Economic burden of asthma multimorbidity in Singapore: Shadow costs of steroid use.The World Allergy Organization journal · 2025Article
- Sociodemographic, health and behavioral factors associated with influenza vaccination uptake among patients with diabetes in Singapore: A cohort registry-based study.Preventive medicine reports · 2025Article
- Preferences for Nonpharmaceutical Interventions During the Endemic Phase of COVID-19: Discrete Choice Experiment.JMIR public health and surveillance · 2025Article
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- Effects of Recent Prior Dengue Infection on Risk and Severity of Subsequent SARS-CoV-2 Infection: A Retrospective Cohort Study.Open forum infectious diseases · 2024Article
- Autoimmune Sequelae After Delta or Omicron Variant SARS-CoV-2 Infection in a Highly Vaccinated Cohort.JAMA network open · 2024Article
- Socioeconomic disadvantage and long-term survival duration in out-of-hospital cardiac arrest patients: A population-based cohort study.Resuscitation plus · 2024Article
- Long-term Cardiovascular, Cerebrovascular, and Other Thrombotic Complications in COVID-19 Survivors: A Retrospective Cohort Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Article
- Associations Between Mean HbA1c, HbA1c Variability, and Both Mortality and Macrovascular Complications in Patients with Diabetes Mellitus: A Registry-Based Cohort Study.Clinical epidemiology · 2023Article
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Abstract
backgroundSocioeconomic status (SES) is an important determinant of health, and SES data is an important confounder to control for in epidemiology and health services research. Individual level SES measures are cumbersome to collect and susceptible to biases, while area level SES measures may have insufficient granularity. The 'Singapore Housing Index' (SHI) is a validated, building level SES measure that bridges individual and area level measures. However, determination of the SHI has previously required periodic data purchase and manual parsing. In this study, we describe a means of SHI determination for public housing buildings with open government data, and validate this against the previous SHI determination method.
methodsGovernment open data sources (e.g. DATA: gov.sg, Singapore Land Authority OneMAP API, Urban Redevelopment Authority API) were queried using custom Python scripts. Data on residential public housing block address and composition from the HDB Property Information dataset (data.gov.sg) was matched to postal code and geographical coordinates via OneMAP API calls. The SHI was calculated from open data, and compared to the original SHI dataset that was curated from non-open data sources in 2018.
resultsTen thousand seventy-seven unique residential buildings were identified from open data. OneMAP API calls generated valid geographical coordinates for all (100%) buildings, and valid postal code for 10,012 (99.36%) buildings. There was an overlap of 10,011 buildings between the open dataset and the original SHI dataset. Intraclass correlation coefficient was 0.999 for the two sources of SHI, indicating almost perfect agreement. A Bland-Altman plot analysis identified a small number of outliers, and this revealed 5 properties that had an incorrect SHI assigned by the original dataset. Information on recently transacted property prices was also obtained for 8599 (85.3%) of buildings.
conclusionSHI, a useful tool for health services research, can be accurately reconstructed using open datasets at no cost. This method is a convenient means for future researchers to obtain updated building-level markers of socioeconomic status for policy and research.
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