We Need More Sex-Disaggregated Data: Unveiling the Data Gap and Showing the Benefit of Sex-Disaggregated Data Along the Health Pathways for Hypertension, Diabetes, HIV and AIDS

Alessandro Feraldi, Sapienza University of Rome
Virginia Zarulli, Department of Statistical Sciences, University of Padova, Italy
Kent Buse, Global Health 50/50, Cambridge, UK
Sarah Hawkes, University College London
Angela Chang, Southern University of Denmark

Sex- and gender-disaggregated health data are critical for understanding the distribution of illnesses, assessing risk exposures, and evaluating healthcare access and utilization. Analysing such data along the health pathway—from risk factor exposure to final health outcomes, including disease prevalence and the care cascade (diagnosis, treatment, and control)—can provide valuable insights into sex- and gender-based health inequities. This study searched for sex- and age-disaggregated data for eight major conditions, but complete care cascade data were found only for hypertension, diabetes, and HIV/AIDS. Across 200 countries, significant sex differences were observed: males generally exhibited higher disease prevalence, mortality rates, and lower rates of healthcare seeking, diagnosis, and treatment adherence compared to females. Smoking prevalence was notably higher among males, while obesity and unsafe sex were more prevalent among females in most countries. These disparities underscore the crucial role of sex-disaggregated data in understanding health inequities and informing gender-responsive interventions. Despite limitations in data availability and completeness, the study highlights the increasing need for more comprehensive and harmonized datasets. Such data are essential for monitoring sex differences and implementing targeted interventions along the health pathway to reduce health inequities and improve outcomes for females and males.

Keywords: Health and Morbidity, Gender Dynamics

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