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Cited by 14Diabetes, Cardiovascular Risks, and LipoproteinsCardiovascular Health and Risk FactorsHealth disparities and outcomes

Racial/ethnic, gender, and age group differences in cardiometabolic risks among adults in a Northern California health plan: a cross-sectional study

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Gordon, Nancy P., Hsueh, Loretta·2021·BMC Public Health
DOI 10.1186/s12889-021-11011-4PMC PMC8235804
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Abstract

Background: In the U.S., the prevalence of diabetes and hypertension are higher among African American/Black (Black), Latinx, and Filipino adults than non-Hispanic White (White) and Chinese adults. We compared the racial/ethnic-specific prevalence of several modifiable cardiometabolic risks in an insured adult population to identify behaviors that may drive racial/ethnic differences in cardiometabolic health. Methods: This cross-sectional study used data for middle-aged (35–64) and older (65–79) Kaiser Permanente Northern California (KPNC) adult health plan members. Smoking status and BMI were derived from electronic health record data. Weighted pooled self-reported data from the 2014/2015 and 2017 KPNC Member Health Survey cycles were used to estimate daily number of servings of fruits/vegetables, general sodium avoidance, sugar-sweetened beverage (SSB) consumption frequency, alcohol use within daily recommended limit, weekly exercise frequency, and number of hours of sleep daily. Age-standardized estimates of all cardiometabolic risks were produced for middle-aged and older-aged women and men in the five racial/ethnic groups. Analyses focused on racial/ethnic differences within age-gender groups and gender and age group differences within racial/ethnic groups. Results: In both age groups, Black, Latinx, and Filipino adults were more likely than White and Chinese adults to have overweight and obesity and were less likely to engage in health promoting dietary (fruit/vegetable and SSB consumption, sodium avoidance (women only)) and sleep behaviors. Middle-aged Black and Filipino men were more likely than White men to be current smokers. Less racial/ethnic variation was seen in exercise frequency. Significant gender differences were observed for dietary behaviors overall and within racial/ethnic groups, especially among middle-aged adults; however, these gender differences were smaller for sleep and exercise. Age differences within gender and racial/ethnic groups were less consistent. Racial/ethnic and gender differences in these behaviors were also seen in the subsample of adults with diabetes and/or hypertension and in the subsample of adults who reported they were trying to engage in health promoting behaviors. Conclusions: Black, Latinx, and Filipino adults were more likely than White and Chinese adults to report dietary and sleep behaviors associated with development and worsening of cardiometabolic conditions, with men exhibiting poorer dietary behaviors than women.

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  • CASPER study results are consistent with existing evidence of higher CVD prevalence among Pacific Islanders and lower prevalence among Asians in comparison to NHWs.

    “However, CASPER study results are consistent with existing evidence of higher CVD prevalence among Pacific Islanders and lower prevalence among Asians in comparison to NHWs [1, 19, 29].”

    From Prevalence of cardiovascular disease among Asian, Pacific Islander and multi-race populations in Hawai’i and California (2023) · cites this paper as [19]

    The Background discusses coronary heart disease in Filipino versus Chinese adults, but does not compare CVD prevalence in Asians with non-Hispanic Whites. A search for Pacific Islanders and CVD prevalence found no passage addressing the claimed comparison with Whites. The Results passages concern cardiometabolic risk factors rather than CVD prevalence. (LLM, conf=0.74)

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Research works printed but not linked: 37

  1. [1]Kurian AK Cardarelli KM Racial and ethnic differences in cardiovascular disease risk factors: a systematic review Ethn Dis 2007 17 1 143 152 17274224
  2. [2]Graham G Disparities in cardiovascular disease risk in the United States Curr Cardiol Rev 2015 11 3 238 245 10.2174/1573403x11666141122220003 25418513 PMC4558355 · DOI
  3. [3]Jones DW Hall JE Racial and ethnic differences in blood pressure: biology and sociology Circulation. 2006 114 25 2757 2759 10.1161/CIRCULATIONAHA.106.668731 17179032 · DOI
  4. [4]Rodriguez JE Campbell KM Racial and ethnic disparities in prevalence and care of patients with type 2 diabetes Clin Diabetes 2017 35 1 66 70 10.2337/cd15-0048 28144049 PMC5241767 · DOI
  5. [5]Pool LR Ning H Lloyd-Jones DM Allen NB Trends in racial/ethnic disparities in cardiovascular health among US adults from 1999–2012 JAHA. 2017 6 9 e006027 10.1161/JAHA.117.006027 28939713 PMC5634269 · DOI
  6. [6]Holland AT Palaniappan LP Problems with the collection and interpretation of Asian-American health data: omission, aggregation, and extrapolation Ann Epidemiol 2012 22 6 397 405 10.1016/j.annepidem.2012.04.001 22625997 PMC4324759 · DOI
  7. [7]Gordon NP Lin TY Rau JL Lo JC Aggregation of Asian-American subgroups masks meaningful differences in health and health risks among Asian ethnicities: an electronic health record based cohort study BMC Public Health 2019 19 1 1551 10.1186/s12889-019-7683-3 31760942 PMC6876105 · DOI · Paper page
  8. [9]Ye J Rust G Baltrus P Daniels E Cardiovascular risk factors among Asian Americans: results from a national health survey Ann Epidemiol 2009 19 10 718 723 10.1016/j.annepidem.2009.03.022 19560369 PMC4905692 · DOI
  9. [10]Huang B Appel HB Nicdao EG Lee HJD Ai AL Chronic conditions, behavioral health, and use of health services among Asian American men: the first nationally representative sample Am J Mens Health 2013 7 1 66 76 10.1177/1557988312460885 22992317 · DOI
  10. [11]Choi SE Liu M Palaniappan LP Wang EJ Wong ND Gender and ethnic differences in the prevalence of type 2 diabetes among Asian subgroups in California J Diabetes Complicat 2013 27 5 429 435 10.1016/jdiacomp.2013.01.002 PMC3769447 23743139 · DOI
  11. [12]Holland AT Wong EC Lauderdale DS Palaniappan LP Spectrum of cardiovascular diseases in Asian-American racial/ethnic subgroups Ann Epidemiol 2011 21 8 608 614 10.1016/j.annepidem.2011.04.004 21737048 PMC3215504 · DOI · Paper page
  12. [13]Lloyd-Jones DM Hong Y Labarthe D Mozaffarian D Appel LJ Van Horn L Greenlund K Daniels S Nichol G Tomaselli GF Arnett DK Fonarow GC Ho PM Lauer MS Masoudi FA Robertson RM Roger V Schwamm LH Sorlie P Yancy CW Rosamond WD American Heart Association Strategic Planning Task Force and Statistics Committee Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association’s strategic impact goal through 2020 and beyond Circulation 2010 121 586 613 10.1161/CIRCULATIONAHA.109.192703 20089546 · DOI · Paper page
  13. [14]Sijtsma FP, Meyer KA, Steffen LM, Shikany JM, Van Horn L, Harnack L, et al. Longitudinal trends in diet and effects of sex, race, and education on dietary quality score change: the Coronary Artery Risk Development in Young Adults study. Am J Clin Nutr. 2012;95(3):580–6. 10.3945/ajcn.111.020719. PMC3278239 22301926 · DOI
  14. [16]Lee M Hu D Bunney G Gadegbeku CA Edmundowicz D Houser SR Wang H Ma GX Health behavior practice among understudied Chinese and Filipino Americans with cardiometabolic diseases Prev Med Rep 2018 11 240 246 10.1016/j.pmedr.2018.06.004 30210996 PMC6129966 · DOI
  15. [17]Pickens CM, Pierannunzi C, Garvin W, Town M. Surveillance for certain health behaviors and conditions among states and selected local areas —Behavioral Risk Factor Surveillance System, United States, 2015. MMWR Surveill Summ. 2018;67(SS-9):1–90. 10.15585/mmwr.ss6709a1. PMC6023179 29953431 · DOI
  16. [18]Hiller J Schatz K Drexler H Gender influence on health and risk behavior in primary prevention: a systematic review J Public Health 2017 25 4 339 349 10.1007/s10389-017-0798-z 32215245 PMC7088168 · DOI · Paper page
  17. [19]Li KK Concepcion RY Lee H Cardinal BJ Ebbeck V Woekel E Readdy RT An examination of sex differences in relation to the eating habits and nutrient intakes of university students J Nutr Educ Behav 2012 44 3 246 250 10.1016/j.jneb.2010.10.002 21764641 · DOI
  18. [20]Watson KB Carlson SA Gunn JP Galuska DA O’Connor A Greenlund KJ Fulton JE Physical inactivity among adults aged 50 years and older — United States, 2014 MMWR Morb Mortal Wkly Rep 2016 65 954 958 10.15585/mmwr.mm6536a3external.icon 27632143 · DOI
  19. [21]Masella R Malorni W Gender-related differences in dietary habits CMI. 2017 11 2 59 62 10.7175/cmi.v11i2.1313 · DOI
  20. [22]Zanjani F Schaie KW Willis S Age group and health status effects on health behavior change Behav Med 2006 32 2 36 46 10.3200/BMED.32.2.36-46 16903613 · DOI
  21. [23]Alley SJ Duncan MJ Schoeppe S Rebar AL Vandelanotte C 8-year trends in physical activity, nutrition, TV viewing time, smoking, alcohol and BMI: a comparison of younger and older Queensland adults PLoS One 2017 12 3 e0172510 10.1371/journal.pone.0172510 28248975 PMC5332140 · DOI
  22. [29]Gordon NP, Lin TY. The Kaiser Permanente Northern California adult Member Health Survey. Perm J. 2016;20(4):15–225. 10.7812/TPP/15-225 E-pub: 08/19/2016. PMC5101088 27548806 · DOI
  23. [30]WHO Expert Consultation Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies Lancet. 2004 363 9403 157 163 10.1016/S0140-6736(03)15268-3 14726171 · DOI · Paper page
  24. [32]Consensus Conference Panel, Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, et al. Joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society on the recommended amount of sleep for a healthy adult: methodology and discussion. Sleep. 2015;38(8):1161–83. 10.5665/sleep.4886. PMC4507722 26194576 · DOI · Paper page
  25. [37]Gordon NP Banegas MP Tucker-Seeley RD Racial-ethnic differences in prevalence of social determinants of health and social risks among middle-aged and older adults in a Northern California health plan PLoS One 2020 15 11 e0240822 10.1371/journal.pone.0240822 33147232 PMC7641349 · DOI
  26. [38]Kiefer I Rathmanner T Kunze M Eating and dieting differences in men and women J Men’s Health Gender 2005 2 2 194 201 10.1016/j.jmhg.2005.04.010 · DOI
  27. [39]Gough B Conner MT Barriers to healthy eating among men: a qualitative analysis Soc Sci Med 2006 62 1 387 395 10.1016/j.socscimed.2005.05.032 16011867 · DOI
  28. [40]Pagoto SL Schneider KL Oleski JL Luciani JM Bodenlos JS Whited MC Male inclusion in randomized controlled trials of lifestyle weight loss interventions Obesity. 2012 20 6 1234 1239 10.1038/oby.2011.140 21633403 · DOI
  29. [41]Shattuck AL White E Kristal AR How women’s adopted low-fat diets affect their husbands Am J Public Health 1992 82 9 1244 1250 10.2105/ajph.82.9.1244 1503166 PMC1694341 · DOI
  30. [42]Allen JO Griffith DM Gaines HC “She looks out for the meals, period”: African American men’s perceptions of how their wives influence their eating behavior and dietary health Health Psychol 2013 32 4 447 455 10.1037/a0028361 22563755 PMC4374446 · DOI
  31. [43]Malik VS Hu FB Sugar-sweetened beverages and cardiometabolic health: an update of the evidence Nutrients 2019 11 8 1840 10.3390/nu11081840 PMC6723421 31398911 · DOI
  32. [45]Malik AH Akram Y Shetty S Malik SS Njike VY Impact of sugar-sweetened beverages on blood pressure Am J Cardiol 2014 113 9 1574 1580 10.1016/j.amjcard.2014.01.437 24630785 · DOI
  33. [46]Brown IJ, Stamler J, Van Horn L, Robertson CE, Chan Q, Dyer AR, et al; International Study of Macro/micronutrients and Blood Pressure Research Group. Sugar-sweetened beverage, sugar intake of individuals, and their blood pressure: international study of macro/micronutrients and blood pressure. Hypertension. 2011;57(4):695–701. 10.1161/HYPERTENSIONAHA.110.165456 Epub 2011 Feb 28. PMC3086758 21357284 · DOI
  34. [47]Xi B He D Zhang M Xue J Zhou D Short sleep duration predicts risk of metabolic syndrome: a systematic review and meta-analysis Sleep Med Rev 2014 18 4 293 297 10.1016/j.smrv.2013.06.001 23890470 · DOI
  35. [48]Li PWC Yu DSF Chong SOK Lin RSY A systematic review on the effects of nonpharmacological sleep interventions on cardiometabolic risk or disease outcomes J Cardiovasc Nurs 2020 35 2 184 198 10.1097/JCN.0000000000000662 31985700 · DOI
  36. [50]Portela LF Rotenberg L Waissmann W Self-reported health and sleep complaints among nursing personnel working under 12 h night and day shifts Chronobiol Int 2004 21 6 859 870 10.1081/cbi-200038513 15646233 · DOI
  37. [51]Groves RM Nonresponse rates and nonresponse bias in household surveys Public Opinion Quarterly 2006 70 5 646 675 10.1093/poq/nfl033 · DOI · Paper page

Cited by

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Authors
Gordon, N. P., & Hsueh, L.
Affiliations
Kaiser Permanente (US)
Corresponding author
Gordon, Nancy P.
ORCID
Venue
BMC Public Health
Publisher
Springer Science and Business Media LLC
Published
2021-06-25
Volume
21
Issue
1
Pages
1227-1227
ISSN
1471-2458 (ISSN-L)
DOI
10.1186/s12889-021-11011-4
PMC
PMC8235804
OpenAlex
W3173842623
Cited by
14
References
5
Citations by year
2026: 1 · 2025: 2 · 2024: 2 · 2023: 7 · 2022: 2
FWCI
2.05
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Public Health (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Kaiser Permanente
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
  • Social Sciences › Health › Health disparities and outcomes
Keywords
cardiometabolic risk, racial and ethnic disparities, gender differences, age differences, diabetes mellitus, hypertension, obesity, smoking, dietary behavior, fruit and vegetable intake, sugar-sweetened beverage consumption, sodium intake, sleep, physical activity, health-promoting behaviors, Kaiser Permanente Northern California
MeSH terms
Adult, Aged, California, Cardiovascular Diseases, Cross-Sectional Studies, Ethnicity, Female, Hispanic or Latino, Humans, Male, Middle Aged, Racial Groups

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