{"doi":"10.1093/geront/gnaf177","title":"A dynamic microsimulation of health outcomes in Mexico’s aging population","abstract":"BACKGROUND AND OBJECTIVES: Mexico faces health policy challenges because of rising prevalence of health conditions, a rapidly aging population, and disparities in health care access. Nationally representative longitudinal surveys released in recent years allow for projections of health care needs that can support policymakers to mitigate these challenges. This study validates the Mexico Future Older Adult Model (MFOAM), a dynamic microsimulation model for Mexico's aging population. Using 2012-2018 data from individuals aged 51+ years in the Mexican Health and Aging Study (MHAS), the simulation builds on the Future Elderly Model from the United States. RESEARCH DESIGN AND METHODS: The model predicts lifetime health outcomes and risk factors, functional limitations, and mortality. Internal validation compares simulation outcomes to survey data at the individual and cohort level. External validation compares outcomes with 2012-2021 data from the National Health and Nutrition Survey (ENSANUT). RESULTS: Internal and external validation showed robust performance. Population projections indicated almost a doubling of the 51+ population in Mexico between 2018 and 2051, with increasing prevalence of hypertension (52.3% to 66.1%), diabetes (24.6% to 31.9%), respiratory disease (10.2% to 15.1%), myocardial infarction (5.5% to 9.7%), stroke (4.3% to 8.0%), cancer (3.6% to 7.0%), and functional limitations (6.6% to 10.2%), reflecting national health trends. DISCUSSION AND IMPLICATIONS: The MFOAM projects population outcomes through 2051, or specific age cohorts until all members reach the end of their lives. Harmonized variables from the Gateway to Global Aging allow for cross-country comparisons and expansion with other health and economic variables. These forecasts help support policy planning and health care strategies in Mexico.","journal":"The Gerontologist","year":2025,"id":546318,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8145,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":668222,"name":"Tadeja Gračner","orcid":"0009-0003-1285-4468","position":1,"is_corresponding":false},{"id":516691,"name":"Bryan Tysinger","orcid":"0000-0002-8497-3664","position":2,"is_corresponding":false},{"id":1392883,"name":"Hanke Heun‐Johnson","orcid":"0000-0002-4101-2492","position":0,"is_corresponding":true}],"reference_count":41,"raw_metadata":null,"created_at":"2026-07-19T02:53:32.285899Z","pmid":"40838876","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}