【正文】 ventative health care. Urban populations can also use higher ines to invest in health through health care, a nutritious diet or by reducing strenuous work effort(Moore et al, 2021).In this paper, we estimate the effect of urbanization on health using longitudinal data from the China Health and Nutrition Survey (CHNS). Besides being a household panel, this survey also collects data on the characteristics of munities, making it possible to identify what happens to individuals? health when the environment in which they live bees more urbanized. This identification strategy avoids the selection biases that arise from parisons between the health of urban and rural populations, or from monitoring the health of migrants, which is difficult or impossible in any case with most panel data. A dichotomous urbanrural classification, most often done on the basis of population density, does not capture the variation in living and health conditions across areas at different stages of urbanization (McDade and Adair, 2021。 Wang and Smith, 2021。 Woods, 1985, 2021). The most likely explanation for this difference in the urbanrural health disparity over time and space is the marked decline in the prevalence of infectious diseases, in lowine as well as highine countries (Riley, 2021), prompted, in large part, by public health measures built on the germ theory of disease (Preston, 1975, 1980。The Health Penalty of China’s Rapid Rapid urbanization could have positive and negative health effects, such that the impact on population health is not obvious. It is, however, highly pertinent to the human welfare consequences of development. This paper uses munity and individual level longitudinal data from the China Health and Nutrition Survey to estimate the health impact of China?s unprecedented urbanization. We construct an index of urban city from a broad set of munity characteristics and define urbanization in terms of movements across the distribution of this index. We use differenceindifferences estimators to identify the treatment effect of urbanization on the selfassessed health of individuals. The results reveal important, and robust, negative causal effects of urbanization on health. Urbanization increases the probability of reporting fair or poor health by 5 to 15 percentage points, with a greater degree of urbanization having larger health effects. While people in more urbanized areas are, on average, in better health than their rural counterparts, the process of urbanization is damaging to health. Our measure of selfassessed health is highly correlated with subsequent mortality and the causal harmful effect of urbanization on health is confirmed using more objective (but also more specific) health indicators, such as physical impairments, disease symptoms and hypertension. Urbanization and economic development are intimately related (Williamson, 1988). There is no better example of this than China in recent decades, where a remarkable rate of economic growth has been acpanied by a process of urbanization that is unprecedented in human history, both in scale and in speed. The proportion of the Chinese population living in urban areas increased from only 20% in 1980, to 27% in 1990, and reached 43% in 2021 (NBS, 2021。 Zimmer et al, 2021). This apparent urban health advantage contrasts with the historical evidence of urban populations suffering poorer health in Western Europe prior to and during its period of industrialization (Rosen, 1958。 Soars, 2021). In the past, the opportunities for material gain offered by cities had to be weighed against the dangers of infection. Today, while cities of the developing world continue to pose risks to health, the immediate threat to life through infection has receded. However, the overcrowding and pollution that acpany urbanization, particularly on the scale and speed with which it has occurred in China, may impose an urban health penalty. During the last decades, China?s environment has deteriorated significantly as rapid urbanization and industrialization generate enormous volumes of air and water pollutants (World Bank, 1997。Wang, Mi et al, 2021。 Dahly and Adair, 2021). In addition, there is a practical problem in that the categorization of an area as ?urban? or ?rural? is often fixed over waves of a longitudinal survey, as it is in the CHNS, and so this categorization does not capture the urbanization taking place. In order to identify munities at various stages of the urbanization process, and to track changes over time in the degree of urban city within each munity, we exploit the CHNS data on the characteristics of munities to construct an index of urbanicity, which depends, for example, on population size, the proportion of the workforce engaged in agriculture, proximity to health and educational facilities, and the presence of paved roads, shops, restaurants, etc. This index has been shown to outperform the simple urbanrural classification that es with the CHNS in detecting different degrees of urbanicity, measuring changes in urbanicity over time and being less prone to misclassification bias (Van de Pole et al, 2021). We define urbanization in terms of movement of a munity up the distribution of this urbanicity index. We adopt a treatment effects framework and define treatment as movement from the bottom to the top half of the distribution of the index. To investigate whether the health impact varies with the degree of urbanization, we also define ordinal treatments in terms of movements up textiles of the distribution and by standard deviation increases in the index. We use differenceindifferences estimators made robust to unobserved individual heterogeneity by exploiting the panel nature of the data (Blundell and Costa Dias, 2021。 the index correlates with a subjective classification of munities