D L Armstrong1, D Strogatz, R Wang. 1. Department of Epidemiology, SPH, University at Albany, SUNY, New York 12144, USA. dla02@health.state.ny.us
Abstract
STUDY OBJECTIVE: Examine the association between county occupational structure, services availability, prevalence of risk factors, and coronary mortality rates by sex, for 1980-96, in New York state. DESIGN: New York's 62 counties were classified into three occupational structure categories; counties with the lowest percentages of the labour force in managerial, professional, and technical occupations were classified in category I, counties with the highest percentages were in category III. Directly age adjusted coronary heart disease (CHD) mortality rates, aged 35-64 years, (from vital statistics and census data), per capita services (Census County Business Patterns), and the prevalence of CHD risk factors (BRFSS data) were calculated for each occupational structure category. RESULTS: CHD mortality rates and the prevalence of risk factors were inversely associated with occupational structure for men and women. Income from manufacturing jobs declined most in category I and per capita numbers of producer services for banking, business credit, overall business services, and personnel/employment services were 9-15 times greater in category III compared with I counties. Consumer services such as grocery stores, fitness facilities, doctors offices, and social services were 1.5-4 times greater in category III compared with I counties. CONCLUSIONS: An ecological model for conceptualizing communities and health and for intervention design is discussed; key community characteristics are occupational and industrial structure, availability and diversity of consumer services, prevalence of health practices, and level of premature CHD.
STUDY OBJECTIVE: Examine the association between county occupational structure, services availability, prevalence of risk factors, and coronary mortality rates by sex, for 1980-96, in New York state. DESIGN: New York's 62 counties were classified into three occupational structure categories; counties with the lowest percentages of the labour force in managerial, professional, and technical occupations were classified in category I, counties with the highest percentages were in category III. Directly age adjusted coronary heart disease (CHD) mortality rates, aged 35-64 years, (from vital statistics and census data), per capita services (Census County Business Patterns), and the prevalence of CHD risk factors (BRFSS data) were calculated for each occupational structure category. RESULTS: CHD mortality rates and the prevalence of risk factors were inversely associated with occupational structure for men and women. Income from manufacturing jobs declined most in category I and per capita numbers of producer services for banking, business credit, overall business services, and personnel/employment services were 9-15 times greater in category III compared with I counties. Consumer services such as grocery stores, fitness facilities, doctors offices, and social services were 1.5-4 times greater in category III compared with I counties. CONCLUSIONS: An ecological model for conceptualizing communities and health and for intervention design is discussed; key community characteristics are occupational and industrial structure, availability and diversity of consumer services, prevalence of health practices, and level of premature CHD.