Associations between Area-Level Unemployment, Body Mass Index, and Risk Factors for Cardiovascular Disease in an Urban Area
Abstract
:Introduction:
Methods:
Results:
Conclusions:
1. Introduction
2. Methods
2.1. Population and Setting
2.2. Outcome Measures
2.3. Exposure Measures and Covariates
2.3.1. Area Level Measures
2.3.2. Individual Level Measures
2.4. Statistical Analysis
3. Results
3.1. Descriptive Statistics
3.2 Associations between ALU, BMI, and TCR
3.2.1. Body Mass Index
3.2.2. Total Cardiometabolic Risk
3.2.3. Gender Stratified Analysis
4. Discussion
Acknowledgments
- Competing InterestsNone
- FundingData collection was provided in equal parts through the (i) Canada Research Chairs program and the Canada Foundation for Innovation (grant #201252, MD), (ii) Canadian Institutes of Health Research (grant # 200203 MOP 57805, LG), and (iii) Fonds de la Recherche en Santé du Québec (FRSQ) (team grant # 8394, LD). At the time of this research, AIN was supported by a Canada Graduates Scholarship Master’s Award from the Canadian Institutes of Health Research. MD was supported by a Canada Research Chair for Biopsychosocial Pathways in Population Health, awarded by the Canadian Institutes of Health Research. CP was supported by a postdoctoral fellowship from the Fonds de la Recherche en Santé du Québec. LG holds a Canadian Institutes of Health Research/Centre de Recherche en Prevention de l’Obésité Applied Public Health Chair in Neighbourhoods, Lifestyle, and Healthy Body Weight. The funding sources did not participate in study design, data collection, analysis or interpretation, writing of the report, or in the decision to submit the paper for publication.
References
- Dawber, T; Meadors, G; Moore, F. Epidemiological approaches to heart disease: the Framingham Study. Am. J. Public Health 1951, 41, 279–286. [Google Scholar]
- Chronic Diseases and their Common Risk Factors, Facing the Facts; World Health Organization: Geneva, Switzerland, 2005.
- Davey-Smith, G; Hart, C; Watt, G; Hole, D; Hawthorne, V. Individual social class, area-based deprivation, cardiovascular disease risk factors, and mortality: the Renfrew and Paisley Study. J. Epidemiol. Community Health 1998, 52, 399–405. [Google Scholar]
- Diez-Roux, AV; Nieto, FJ; Caulfield, L; Tyroler, HA; Watson, RL; Szklo, M. Neighbourhood differences in diet: the Atherosclerosis Risk in Communities (ARIC) Study. J. Epidemiol. Community Health 1999, 53, 55–63. [Google Scholar]
- Janssen, I; Boyce, WF; Simpson, K; Pickett, W. Influence of individual- and area-level measures of socioeconomic status on obesity, unhealthy eating, and physical inactivity in Canadian adolescents. Am. J. Clin. Nutr 2006, 83, 139–145. [Google Scholar]
- Morland, K; Wing, S; Diez-Roux, AV. The contextual effect of the local food environment on residents’ diets: the atherosclerosis risk in communities study. Am. J. Public Health 2002, 92, 1761–1768. [Google Scholar]
- Shishehbor, MH; Gordon-Larsen, P; Kiefe, CI; Litaker, D. Association of neighbourhood socioeconomic status with physical fitness in healthy young adults: The Coronary Artery Risk Development in Young Adults (CARDIA) study. Am. Heart J 2008, 155, 699–705. [Google Scholar]
- Franzini, L; Spears, W. Contributions of social context to inequalities in years of life lost to heart disease in Texas, USA. Soc. Sci. Med 2003, 57, 1847–1861. [Google Scholar]
- Diez-Roux, AV; Merkin, SS; Arnett, D; Chambless, L; Massing, M; Nieto, JF; Sorlie, P; Szklo, M; Tyroler, HA; Watson, RL. Neighbourhood of residence and incidence of coronary heart disease. N. Engl. J. Med 2001, 345, 99–106. [Google Scholar]
- McKinlay, JB. Some contributions from the social system to gender inequalities in heart disease. J. Health Soc. Behav 1996, 37, 1–26. [Google Scholar]
- Molinari, C; Ahern, M; Hendryx, M. The relationship of community quality to the health of women and men. Soc. Sci. Med 1998, 47, 1113–1120. [Google Scholar]
- Diez-Roux, AV; Nieto, FJ; Muntaner, C; Tyroler, HA; Comstock, GW; Shahar, E; Cooper, LS; Watson, RL; Szklo, M. Neighbourhood environments and coronary heart disease: a multilevel analysis. Am. J. Epidemiol 1997, 146, 48–63. [Google Scholar]
- Krieger, N; Williams, DR; Moss, NE. Measuring social class in us public health research: concepts, methodologies, and guidelines. Ann. Rev. Public Health 1997, 18, 341–378. [Google Scholar]
- Oakes, JM; Rossi, PH. The measurement of SES in health research: current practice and steps toward a new approach. Soc. Sci. Med 2003, 56, 769–784. [Google Scholar]
- Kitchen, P. An approach for measuring urban deprivation change: the example of East Montréal and the Montréal Urban Community, 1986–96. Environ. Plan. A 2001, 33, 1901–1921. [Google Scholar]
- Sen, A. Inequality, unemployment and contemporary Europe. Int. Labour Rev 1997, 136, 155. [Google Scholar]
- Health and Social Justice: Politics, Ideology and Inequity in the Distribution of Disease: A Public Health Reader; Hofrichter, R (Ed.) Jossey-Bass: San Francisco, CA, USA, 2003.
- Lindbeck, A. Unemployment and Macroeconomics; The MIT Press: Cambridge, MA, USA, 1993. [Google Scholar]
- Dragano, N; Bobak, M; Wege, N; Peasey, A; Verde, PE; Kubinova, R; Weyers, S; Moebus, S; Möhlenkamp, S; Stang, A; Erbel, R; Jöckel, KH; Siegrist, J; Pikhart, H. Neighbourhood socioeconomic status and cardiovascular risk factors: a multilevel analysis of nine cities in the Czech Republic and Germany. BMC Public Health 2007, 7, 255. [Google Scholar]
- Ross, NA; Tremblay, S; Khan, S; Crouse, D; Tremblay, M; Berthelot, J-M. Body Mass Index in urban Canada: neighbourhood and metropolitan area effects. Am. J. Public Health 2007, 97, 500–508. [Google Scholar]
- Wang, MC; Kim, S; Gonzalez, AA; MacLeod, KE; Winkleby, MA. Socioeconomic and food-related physical characteristics of the neighbourhood environment are associated with body mass index. J. Epidemiol. Community Health 2007, 61, 491–498. [Google Scholar]
- Zunzunegui, M-V; Forster, M; Gauvin, L; Raynault, M-F; Douglas, JW. Community unemployment and immigrants’ health in Montreal. Soc. Sci. Med 2006, 63, 485–500. [Google Scholar]
- Sundquist, K; Theobald, H; Yang, M; Li, X; Johansson, S-E; Sundquist, J. Neighbourhood violent crime and unemployment increase the risk of coronary heart disease: a multilevel study in an urban setting. Soc. Sci. Med 2006, 62, 2061–2071. [Google Scholar]
- Hayne, CL; Moran, PA; Ford, MM. Regulating environments to reduce obesity. J. Public Health Policy 2004, 25, 391–407. [Google Scholar]
- Daniel, M; Moore, S; Kestens, Y. Framing the biosocial pathways underlying associations between place and cardiometabolic disease. Health Place 2008, 14, 117–132. [Google Scholar]
- Coulton, C; Korbin, J; Chan, T; Su, M. Mapping residents’ perceptions of neighbourhood boundaries: a methodological note. Am. J. Community Psychol 2001, 29, 371–383. [Google Scholar]
- Tobler, W. A computer movie simulating urban growth in the Detroit region. Econ. Geogr 1970, 46, 234–240. [Google Scholar]
- Chaix, B; Merlo, J; Subramanian, SV; Lynch, J; Chauvin, P. Comparison of a spatial perspective with the multilevel analytical approach in neighbourhood studies: the case of mental and behavioral disorders due to psychoactive substance use in Malmo, Sweden, 2001. Am. J. Epidemiol 2005, 162, 171–182. [Google Scholar]
- Kestens, Y; Thériault, M; Des Rosiers, F. Heterogeneity in hedonic modelling of house prices: looking at buyers’ household profiles. J. Geogr. Syst 2006, 8, 61–96. [Google Scholar]
- Moore, S; Daniel, M; Gauvin, L; Dubé, L. Not all social capital is good capital. Health Place 2009, 15, 1071–1077. [Google Scholar]
- Moore, S; Daniel, M; Paquet, C; Dubé, L; Gauvin, L. Association of individual network social capital with abdominal adiposity, overweight and obesity. J. Public Health 2009, 31, 175–183. [Google Scholar]
- Pearson, TA; Blair, SN; Daniels, SR; Eckel, RH; Fair, JM; Fortmann, SP; Franklin, BA; Goldstein, LB; Greenland, P; Grundy, SM; Hong, Y; Houston, M; Lauer, N; Ockene, RM; Sacco, IS; Sallis, RL; Smith, JF, Jr; Sidney, C, Jr; Stone, NJ; Taubert, KA. AHA guidelines for primary prevention of cardiovascular disease and stroke: 2002 update: consensus panel guide to comprehensive risk reduction for adult patients without coronary or other atherosclerotic vascular diseases. Circulation 2002, 106, 388–391. [Google Scholar]
- Daniel, M; Kestens, Y. MEGAPHONE (®1046898): Montreal Epidemiological and Geographic Analysis of Population Health Outcomes and Neighbourhood Effects, Canada Registered Copyright 2007 (no. 1046898), 2008.
- Census Tract Profile for 0304.00, Montréal, Quebec (table). 2006 Census Tract (CT) Profiles; Stasitics Canada: Ottawa, ON, Canada, 2007.
- Serdula, M; Coates, R; Byers, T; Mokdad, A; Jewell, S; Chavez, N; Mares-Perlman, J; Newcomb, P; Ritenbaugh, C; Treiber, F; Block, G. Evaluation of a brief telephone questionnaire to estimate fruit and vegetable consumption in diverse study populations. Epidemiology 1993, 4, 455–463. [Google Scholar]
- Pérez, C. Fruit and vegetable consumption. Health Rep 2003, 13, 23–31. [Google Scholar]
- United States Department of Agriculture, Dietary Guidelines for Americans; USDA/HHS: Washington, DC, USA, 2005.
- Statistical Package for the Social Sciences; SPSS: Chicago, IL, USA, 2005.
- Hanley, JA; Negassa, A; Edwardes, MD; Forrester, JE. Statistical analysis of correlated data using generalized estimating equations: an orientation. Am. J. Epidemiol 2003, 157, 364–375. [Google Scholar]
- Kobetz, E; Daniel, M; Earp, J. Neighbourhood poverty and self-reported health among low-income, rural women, 50 years and older. Health Place 2003, 9, 263–271. [Google Scholar]
- Norušis, MJ. SPSS 150 Advanced Statistical Procedures Companion; Prentice Hall: Upper Saddle River, NJ, USA, 2006. [Google Scholar]
- Stevens, J; Cai, J; Pamuk, ER; Williamson, DF; Thun, MJ; Wood, JL. The effect of age on the association between body-mass index and mortality. N. Engl. J. Med 1998, 338, 1–7. [Google Scholar]
- Rowland, ML. Self-reported weight and height. Am. J. Clin. Nutr 1990, 52, 1125–1133. [Google Scholar]
- Ellaway, A; Macintyre, S. Women in their place: gender and perceptions of neighbourhoods in the West of Scotland. In Geographies of Women’s Health; Dyck, I, Lewis, ND, McLafferty, S, Eds.; Routledge: London, UK, 2001; pp. 265–281. [Google Scholar]
- Duncan, C; Jones, K; Moon, G. Context, composition and heterogeneity: using multilevel models in health research. Soc. Sci. Med 1998, 46, 97–117. [Google Scholar]
- Marmot, MG; Fuhrer, R; Ettner, SL; Marks, NF; Bumpass, LL; Ryff, CD. Contribution of psychosocial factors to socioeconomic differences in health. Milbank Q 1998, 76, 403–448. [Google Scholar]
- Etter, J-F; Perneger, TV. Analysis of non-response bias in a mailed health survey. J. Clin. Epidemiol 1997, 50, 1123–1128. [Google Scholar]
- McDonal, JT; Kennedy, S. Is migration to Canada associated with unhealthy weight gain? Overweight and obesity among Canada’s immigrants. Soc. Sci. Med 2005, 61, 2469–2481. [Google Scholar]
- Cubbin, C; Sundquist, K; Ahlen, H; Johansson, S-E; Winkleby, MA; Sundquist, J. Neighbourhood deprivation and cardiovascular disease risk factors: protective and harmful effects. Scand. J. Public Health 2006, 34, 228–237. [Google Scholar]
- Kawachi, I; Berkman, LF. Neighbourhoods and Health; Oxford University Press: Oxford, UK, 2001. [Google Scholar]
Men (n = 169) | Women (n = 173) | |
---|---|---|
Continuous Variables | Mean (Std Dev) | Mean (Std Dev) |
BMI (kg/m2) | 25.1 (3.9) | 24.6 (5.2) |
Age (years) | 35.8 (8.9) | 33.9 (8.5) |
Weekly energy expenditure (METS) | 1348.6 (1052.2) | 1063.8 (856.5) |
Fruit & Vegetable Consumption (Max = 40) | 13.2 (4.9) | 14.2 (4.1) |
Categorical Variables | N (%) | N (%) |
---|---|---|
Unemployed | ||
Yes | 27 (16.0) | 13 (7.5) |
No | 142 (84.0) | 160 (92.5) |
Area-Level Unemployment | ||
Quartile 4 | 33 (19.5) | 43 (24.9) |
Quartile 3 | 45 (26.6) | 48 (27.7) |
Quartile 2 | 47 (27.8) | 48 (27.7) |
Quartile 1 | 44 (26.0) | 34 (19.7) |
Fast Food Consumption | ||
Yes | 87 (51.5) | 61 (35.3) |
No | 82 (48.5) | 112 (64.7) |
Smoker | ||
Never smoker/former smoker | 113 (66.9) | 125 (72.3) |
Smoker | 56 (33.1) | 48 (27.7) |
Education | ||
Less than high school | 9 (5.3) | 18 (10.4) |
High-School completed | 35 (20.7) | 26 (15.0) |
Trade school or university | 125 (74.0) | 129 (74.6) |
Alcohol Consumption | ||
Abstainer | 55 (32.5) | 64 (37.0) |
Moderate | 80 (47.3) | 97 (56.1) |
Heavy | 33 (19.5) | 11 (6.4) |
Income | ||
Below $20K (CAD) | 44 (26.0) | 57 (32.9) |
Between $20K & 50K (CAD) | 61 (36.1) | 52 (30.1) |
Above $50K (CAD) | 64 (37.9) | 64 (37.0) |
Total Cardiovascular Risk | ||
0 no indicator exceeding risk value | 39 (22.8) | 62 (35.8) |
1 indicator exceeding risk value | 51 (29.8) | 73 (42.2) |
2 indicators exceeding risk value | 44 (25.7) | 28 (16.2) |
3 indicators exceeding risk value | 28 (16.4) | 9 (5.2) |
4 indicators exceeding risk value | 7 (4.1) | 1 (0.6) |
Model 1† | Model 2a‡ | Model 3§ | Model 4# | ||
---|---|---|---|---|---|
Beta (95% CI) | Beta (95% CI) | Beta (95% CI) | Beta (95% CI) | ||
BMI | ALU4* | 2.69 (2.40, 3.00) | 3.19 (2.39, 3.99) | 2.71 (1.93, 3.49) | 2.11 (1.03, 3.19) |
ALU3 | 1.67 (1.12, 2.22) | 2.16 (1.71, 2.61) | 1.71 (1.14, 2.78) | 1.51 (0.55, 2.47) | |
ALU2 | 0.50 (0.11, 0.90) | 1.56 (0.46, 2.66) | 1.37 (0.59, 2.15) | 1.09 (−0.20, 2.38) | |
PR (95% CI) | PR (95% CI) | PR (95% CI) | PR (95% CI) | ||
TCR | ALU4* | 1.60 (1.47, 1.73) | 2.20 (1.53, 3.17) | 1.85 (1.32, 2.59) | 1.82 (1.35, 2.44) |
ALU3 | 1.50 (1.36, 1.65) | 1.84 (1.44, 2.33) | 1.60 (1.25, 2.04) | 1.66 (1.33, 2.07) | |
ALU2 | 1.16 (1.07, 1.25) | 1.42 (0.99, 2.03) | 1.28 (0.92, 1.77) | 1.37 (0.97, 1.94) |
HDL (95% CI) | TRG (95% CI) | TC (95% CI) | HbA1c (95% CI) | ||
---|---|---|---|---|---|
Model 1† | ALU4 | 2.72 (2.40, 3.08) | 2.52 (2.12, 2.97) | 1.04 (0.62, 1.72) | 1.82 (1.65, 2.01) |
ALU3 | 2.09 (1.31, 3.32) | 1.96 (1.67, 2.3) | 0.765 (0.40, 1.46) | 2.07 (1.88, 2.27) | |
ALU2 | 0.73 (0.58, 0.91) | 0.83 (0.71, 0.95) | 1.346 (0.80, 2.24) | 1.98 (1.73, 2.25) | |
Model 2‡ | ALU4 | 5.93 (2.07, 16.95) | 4.93 (1.64, 14.81) | 1.465 (0.68, 3.12) | 6.32 (3.61, 11.04) |
ALU3 | 4.14 (1.30, 13.15) | 1.97 (1.04, 3.72) | 0.997 (0.58, 1.7) | 2.64 (1.78, 3.89) | |
ALU2 | 0.93 (0.76, 1.12) | 0.98 (0.71, 1.34) | 1.592 (1.01, 2.53) | 2.74 (2.33, 3.21) | |
Model 3§ | ALU4 | 4.85 (1.77, 13.24) | 4.33 (1.38, 13.50) | 0.948 (0.44, 2.00) | 6.13 (2.53, 14.79) |
ALU3 | 3.83 (1.33, 10.96) | 1.93 (1.12, 3.30) | 0.791 (0.49, 1.27) | 2.62 (1.54, 4.42) | |
ALU2 | 0.95 (0.83, 1.07) | 1.05 (0.75, 1.44) | 1.45 (0.98, 2.13) | 2.64 (2.12, 3.26) | |
Model 4# | ALU4 | 4.19 (1.18, 14.84) | 4.51 (1.05, 19.24) | 0.987 (0.46, 2.09) | 7.45 (3.78, 14.68) |
ALU3 | 2.68 (0.82, 8.71) | 1.82 (0.94, 3.52) | 0.778 (0.51, 1.18) | 2.68 (1.55, 4.61) | |
ALU2 | 0.61 (0.46, 0.79) | 0.99 (0.50, 1.92) | 1.404 (1.25, 1.57) | 2.85 (2.19, 3.71) |
BMI | TCR | ||||
---|---|---|---|---|---|
Men | Women | Men | Women | ||
Beta (95% CI) | Beta (95% CI) | PR (95% CI) | PR (95% CI) | ||
Model 1† | ALU4* | 0.8 (0.33, 1.27) | 4.63 (3.94, 5.32) | 1.36 (1.02, 1.81) | 2.1 (1.49, 2.95) |
ALU3 | −0.32 (−1.26, 0.62) | 3.65 (2.87, 4.43) | 1.37 (1.02, 1.83) | 1.58 (1.08, 2.31) | |
ALU2 | −1.7 (−2.27, −1.13) | 2.53 (1.86, 3.20) | 1.20 (0.88, 1.67) | 1.13 (0.76, 1.69) | |
Model 2‡ | ALU4 | 0.96 (−0.96, 2.88) | 5.7 (1.96, 9.44) | 1.85 (1.26, 2.72) | 3.00 (1.10, 8.19) |
ALU3 | −0.53 (−1.73, 0.67) | 4.5 (1.93, 7.07) | 1.56 (1.16, 2.11) | 2.09 (0.83, 5.25) | |
ALU2 | −0.14 (−2.02, 1.74) | 3.08 (0.96, 5.20) | 1.25 (0.77, 2.04) | 1.46 (0.68, 3.12) | |
Model 3§ | ALU4 | 1.45 (−0.82, 3.72) | 4.89 (0.83, 8.95) | 1.64 (1.13, 2.39) | 2.38 (0.98, 5.79) |
ALU3 | 0.18 (−1.2, 1.55) | 3.89 (1.26, 6.52) | 1.42 (1.03, 1.96) | 2.64 (0.67, 4.02) | |
ALU2 | 0.04 (−1.78, 1.86) | 3.18 (0.87, 5.49) | 1.19 (0.71, 2.01) | 1.27 (0.61, 2.64) | |
Model 4# | ALU4 | 1.69 (−0.47, 3.85) | 2.7 (−1.44, 6.85) | 1.61 (1.19, 2.18) | 2.51 (1.12, 5.6) |
ALU3 | 0.57 (−0.80, 1.94) | 2.25 (−1.06, 5.56) | 1.47 (1.18, 1.84) | 1.82 (0.77, 4.28) | |
ALU2 | 0.18 (−2.19, 2.55) | 1.71 (−1.37, 4.79) | 1.26 (0.82, 1.94) | 1.41 (0.74, 2.7) |
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Naimi, A.I.; Paquet, C.; Gauvin, L.; Daniel, M. Associations between Area-Level Unemployment, Body Mass Index, and Risk Factors for Cardiovascular Disease in an Urban Area. Int. J. Environ. Res. Public Health 2009, 6, 3082-3096. https://doi.org/10.3390/ijerph6123082
Naimi AI, Paquet C, Gauvin L, Daniel M. Associations between Area-Level Unemployment, Body Mass Index, and Risk Factors for Cardiovascular Disease in an Urban Area. International Journal of Environmental Research and Public Health. 2009; 6(12):3082-3096. https://doi.org/10.3390/ijerph6123082
Chicago/Turabian StyleNaimi, Ashley Isaac, Catherine Paquet, Lise Gauvin, and Mark Daniel. 2009. "Associations between Area-Level Unemployment, Body Mass Index, and Risk Factors for Cardiovascular Disease in an Urban Area" International Journal of Environmental Research and Public Health 6, no. 12: 3082-3096. https://doi.org/10.3390/ijerph6123082