TY - JOUR
T1 - P85 History, politics and vulnerability
T2 - Society for Social Medicine
AU - Collins, Charles
PY - 2016/9
Y1 - 2016/9
N2 - Background: High levels of excess mortality (i.e. higher mortality over and above that explained by socio-economic deprivation) have been observed for Glasgow in comparison with similar post-industrial cities such as Liverpool and Manchester. Many potential explanations have been suggested. Based on an assessment of these hypotheses, the aim was to develop an understanding of the most likely underlying causes. Methods: Forty hypotheses were examined, including those identified from a systematic review. The relevance of each was assessed by means of Bradford Hill’s criteria for causality, alongside – for hypotheses deemed causally linked to mortality – comparisons of exposures between Glasgow and Liverpool/Manchester. Where important gaps in the evidence base were identified, new research was undertaken/commissioned involving literature reviews, new data collection, and analyses of existing data sets. Relevant hypotheses were further assessed in terms of links to other key risk factors. A series of causal chains was created, each tested in terms of the extent to which it explained the many different facets of excess mortality. The models were further tested with key informants from public health and other disciplines. Results: Key to the explanatory model for Glasgow is that the city was made more vulnerable to important socio-economic (deprivation, deindustrialisation) and political (detrimental economic policies) exposures, resulting in more adverse outcomes. This vulnerability was generated by a series of historical factors/processes including: the lagged effects of historical levels of overcrowding; Scottish Office policy in post-war decades including the socially-selective relocation of population to outside the city; more detrimental processes of urban change resulting in relatively worse living conditions; and differences in local government responses to UK economic policy in the 1980s which conferred protective effects on comparator cities. Further resulting protective factors were identified e.g. greater social capital in Liverpool. Other contributory factors were highlighted, including the inadequate measurement of deprivation. Conclusion: A number of important weaknesses are acknowledged e.g. a lack of available evidence for some hypotheses, and an inability to quantify the effect of each component of the model on excess mortality. Despite this, the work has helped to further understanding of the underlying causes of Glasgow’s excess mortality. The implications for policy include the need to address three issues simultaneously: to protect against key exposures (e.g. poverty) which impact detrimentally across all UK cities; to address the existing consequences of Glasgow’s vulnerability; and to mitigate against the effects of future vulnerabilities which are likely to emerge from UK Government ‘welfare reform’ policies.
AB - Background: High levels of excess mortality (i.e. higher mortality over and above that explained by socio-economic deprivation) have been observed for Glasgow in comparison with similar post-industrial cities such as Liverpool and Manchester. Many potential explanations have been suggested. Based on an assessment of these hypotheses, the aim was to develop an understanding of the most likely underlying causes. Methods: Forty hypotheses were examined, including those identified from a systematic review. The relevance of each was assessed by means of Bradford Hill’s criteria for causality, alongside – for hypotheses deemed causally linked to mortality – comparisons of exposures between Glasgow and Liverpool/Manchester. Where important gaps in the evidence base were identified, new research was undertaken/commissioned involving literature reviews, new data collection, and analyses of existing data sets. Relevant hypotheses were further assessed in terms of links to other key risk factors. A series of causal chains was created, each tested in terms of the extent to which it explained the many different facets of excess mortality. The models were further tested with key informants from public health and other disciplines. Results: Key to the explanatory model for Glasgow is that the city was made more vulnerable to important socio-economic (deprivation, deindustrialisation) and political (detrimental economic policies) exposures, resulting in more adverse outcomes. This vulnerability was generated by a series of historical factors/processes including: the lagged effects of historical levels of overcrowding; Scottish Office policy in post-war decades including the socially-selective relocation of population to outside the city; more detrimental processes of urban change resulting in relatively worse living conditions; and differences in local government responses to UK economic policy in the 1980s which conferred protective effects on comparator cities. Further resulting protective factors were identified e.g. greater social capital in Liverpool. Other contributory factors were highlighted, including the inadequate measurement of deprivation. Conclusion: A number of important weaknesses are acknowledged e.g. a lack of available evidence for some hypotheses, and an inability to quantify the effect of each component of the model on excess mortality. Despite this, the work has helped to further understanding of the underlying causes of Glasgow’s excess mortality. The implications for policy include the need to address three issues simultaneously: to protect against key exposures (e.g. poverty) which impact detrimentally across all UK cities; to address the existing consequences of Glasgow’s vulnerability; and to mitigate against the effects of future vulnerabilities which are likely to emerge from UK Government ‘welfare reform’ policies.
U2 - 10.1136/jech-2016-208064.184
DO - 10.1136/jech-2016-208064.184
M3 - Meeting Abstract
SN - 0143-005X
VL - 70
SP - A91-A91
JO - Journal of Epidemiology and Community Health
JF - Journal of Epidemiology and Community Health
IS - Suppl, 1
Y2 - 14 September 2016 through 16 September 2016
ER -