The difficult economic times that Cuba has had to fare have taken a conside
rable toll on its urban ecosystems, with data suggesting that indicators of
health, the environment, and social services have been deteriorating. This
has been particularly evident in Centro Habana, a municipality with the hi
ghest population density in the country. More than half the population was
without daily access to potable water, waste disposal was insufficient, ove
rcrowding was serious, disease vectors were prevalent, and rates of various
infectious as well as noncommunicable diseases and injuries were highest i
n the country. To improve the situation, the municipality requested help fr
om the National Institute for Hygiene Epidemiology and Microbiology (INHEM)
to determine the best use of scarce resources to improve health. INHEM per
formed an ecological descriptive study and conducted focus groups in five c
ommunities to assess perceptions of health, social, and environmental facto
rs, followed by a household survey. INHEM then engaged collaborators at the
University of Manitoba to assist in developing a framework, analyzing the
data, and planning and undertaking the evaluation requested. Maximum likeli
hood factor analysis was used to reduce the dimensionality of the data. The
perception data were then merged with the ecological level health and envi
ronmental data to ascertain the relationship between these two data sources
and determine which indicators might be useful for an intervention analysi
s. The perception results indicated that the greatest community concern was
quality of housing, but that the risk perception results were independent
of ecological data on morbidity, mortality, and basic sanitation indicators
. Based on this conclusion, it was decided to use a combined qualitative an
d quantitative approach to evaluate actual and potential interventions, usi
ng the driving force-pressure-state-exposure-effects-action (DPSEEA) framew
ork. It was also decided to adopt an ecosystem approach that fully involves
the community in developing a set of ecosystem human health indicators. Da
ta from repeat focus groups and household surveys are planned, with these d
ata to again be integrated with ecological data including environmental, so
cioeconomic, and health outcome information, using a pre- versus postinterv
ention with concurrent control design. Our findings in this first phase ind
icated that an ecosystem framework is invaluable in ascertaining determinan
ts of health and prioritizing and evaluating interventions to improve the h
ealth of communities.