Ignite Creation Date:
2024-05-05 @ 11:26 AM
Last Modification Date:
2024-10-26 @ 9:08 AM
Study NCT ID:
NCT00046657
Status:
COMPLETED
Last Update Posted:
2016-07-29
First Post:
2002-09-30
Brief Title:
Longitudinal Study of Neighborhood Predictors of CVD
Sponsor:
National Heart Lung and Blood Institute NHLBI
Organization:
National Heart Lung and Blood Institute NHLBI
Study Overview
Official Title:
None
Status:
COMPLETED
Status Verified Date:
2008-01
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
To examine how neighborhood-level factors interact with individual characteristics to predict incidence of cardiovascular disease and all-cause mortality
Detailed Description:
BACKGROUND
There are few comprehensive databases that allow for a longitudinal examination of how neighborhood-level factors may interact with individual characteristics to predict incident cases of cardiovascular disease CVD and all-cause mortality This cross-institutional project joins investigators from Karolinska Institutet in Sweden and Stanford University known for their expertise in immigrant health and social inequalities in CVD
DESIGN NARRATIVE
The study examines how neighborhood social characteristics eg neighborhood socioeconomic status SES social disintegration socioeconomic and ethnic segregation social capital physical environments eg geocoded assets including goods and services contributing to health such as educational and recreational resources barriers to health including pollution industries waste dumps criminal activity alcohol and fast food outlets and individual factors eg SES cardiovascular disease CVD risk factors country of birth and social networks may interrelate to predict CVD morbidity and mortality and all-cause mortality Data will be used from a newly created comprehensive set of Swedish databases MigMed and MigSALLS MigMed 1990-2002 includes data for the entire Swedish population of 6 million women and men aged 25 and older of whom 600000 are first generation immigrants Their addresses have been geocoded yielding 9677 neighborhoods which will be reduced to a smaller number of defined units by cluster analyses MigMed includes an annual assessment of individual-level sociodemographic and health indicators Data will also be analyzed from MigSALLS 1988-2002 which includes more in-depth data from face-to-face interviews with a representative sample of approximately 18000 women and men aged 25-74 of whom 2000 are first generation immigrants MigSALLS contains similar individual- and neighborhood-level factors as MigMed as well as extensive information on factors that may mediate relationships between neighborhoods and CVD outcomes eg CVD risk factors such as smoking weight physical activity and blood pressure Information from these two datasets will be matched to hospital and death records 300000 deaths and 140000 incidence cases of CVD expected between 1988-2002 thus creating one of the largest databases in the world involving men and women from diverse SES levels and countries of origin
There are few comprehensive databases that allow for a longitudinal examination of how neighborhood-level factors may interact with individual characteristics to predict incident cases of cardiovascular disease CVD and all-cause mortality This cross-institutional project joins investigators from Karolinska Institutet in Sweden and Stanford University known for their expertise in immigrant health and social inequalities in CVD
DESIGN NARRATIVE
The study examines how neighborhood social characteristics eg neighborhood socioeconomic status SES social disintegration socioeconomic and ethnic segregation social capital physical environments eg geocoded assets including goods and services contributing to health such as educational and recreational resources barriers to health including pollution industries waste dumps criminal activity alcohol and fast food outlets and individual factors eg SES cardiovascular disease CVD risk factors country of birth and social networks may interrelate to predict CVD morbidity and mortality and all-cause mortality Data will be used from a newly created comprehensive set of Swedish databases MigMed and MigSALLS MigMed 1990-2002 includes data for the entire Swedish population of 6 million women and men aged 25 and older of whom 600000 are first generation immigrants Their addresses have been geocoded yielding 9677 neighborhoods which will be reduced to a smaller number of defined units by cluster analyses MigMed includes an annual assessment of individual-level sociodemographic and health indicators Data will also be analyzed from MigSALLS 1988-2002 which includes more in-depth data from face-to-face interviews with a representative sample of approximately 18000 women and men aged 25-74 of whom 2000 are first generation immigrants MigSALLS contains similar individual- and neighborhood-level factors as MigMed as well as extensive information on factors that may mediate relationships between neighborhoods and CVD outcomes eg CVD risk factors such as smoking weight physical activity and blood pressure Information from these two datasets will be matched to hospital and death records 300000 deaths and 140000 incidence cases of CVD expected between 1988-2002 thus creating one of the largest databases in the world involving men and women from diverse SES levels and countries of origin
Study Oversight
Has Oversight DMC:
Is a FDA Regulated Drug?:
Is a FDA Regulated Device?:
Is an Unapproved Device?:
Is a PPSD?:
Is a US Export?:
Is an FDA AA801 Violation?:
Secondary IDs
| Secondary ID | Type | Domain | Link |
|---|---|---|---|
| R01HL071084 | NIH | None | httpsreporternihgovquickSearchR01HL071084 |