Leveraging mobile phones to attain sustainable development.
Valentina RotondiRidhi KashyapLuca Maria PesandoSimone SpinelliFrancesco C BillariPublished in: Proceedings of the National Academy of Sciences of the United States of America (2020)
For billions of people across the globe, mobile phones enable relatively cheap and effective communication, as well as access to information and vital services on health, education, society, and the economy. Drawing on context-specific evidence on the effects of the digital revolution, this study provides empirical support for the idea that mobile phones are a vehicle for sustainable development at the global scale. It does so by assembling a wealth of publicly available macro- and individual-level data, exploring a wide range of demographic and social development outcomes, and leveraging a combination of methodological approaches. Macro-level analyses covering 200+ countries reveal that mobile-phone access is associated with lower gender inequality, higher contraceptive uptake, and lower maternal and child mortality. Individual-level analyses of survey data from sub-Saharan Africa, linked with detailed geospatial information, further show that women who own a mobile phone are better informed about sexual and reproductive health services and empowered to make independent decisions. Payoffs are larger among the least-developed countries and among the most disadvantaged micro-level clusters. Overall, our findings suggest that boosting mobile-phone access and coverage and closing digital divides, particularly among women, can be powerful tools to attain empowerment-related sustainable development goals, in an ultimate effort to enhance population health and well-being and reduce poverty.
Keyphrases
- mental health
- healthcare
- health information
- primary care
- polycystic ovary syndrome
- electronic health record
- gene expression
- public health
- type diabetes
- big data
- risk factors
- body mass index
- cross sectional
- single cell
- metabolic syndrome
- cardiovascular events
- physical activity
- deep learning
- quality improvement
- insulin resistance
- adipose tissue
- artificial intelligence
- weight gain
- weight loss
- drug induced