International Journal of Hypertension

International Journal of Hypertension / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 2401747 | https://doi.org/10.1155/2020/2401747

Vincent L. Mendy, Rodolfo Vargas, Oluwabunmi Ogungbe, Lei Zhang, "Hypertension among Mississippi Workers by Sociodemographic Characteristics and Occupation, Behavioral Risk Factor Surveillance System", International Journal of Hypertension, vol. 2020, Article ID 2401747, 6 pages, 2020. https://doi.org/10.1155/2020/2401747

Hypertension among Mississippi Workers by Sociodemographic Characteristics and Occupation, Behavioral Risk Factor Surveillance System

Academic Editor: Kwok Leung Ong
Received15 Mar 2020
Revised02 Jun 2020
Accepted22 Jun 2020
Published17 Jul 2020

Abstract

In 2017, Mississippi had the third highest age-adjusted prevalence of hypertension in the United States. We estimated the prevalence of hypertension by sociodemographic characteristics and occupation and examined the association between hypertension with occupation and sociodemographic characteristics among Mississippi workers. We calculated adjusted prevalence and adjusted prevalence ratios (APRs) by sociodemographic characteristics and occupation among Mississippi adult workers. We analyzed combined 2013, 2015, and 2017 data from the Mississippi Behavioral Risk Factor Surveillance System for 6,965 workers in ten Standard Occupational Classification System major groups. Of the estimated 1.1 million Mississippi workers during the three survey years, 31.4% (95% confidence interval (CI), 30.0–32.8) had hypertension. The likelihood of having hypertension was significantly higher among workers aged 30–44 years, 45–64 years, blacks, and those classified as overweight and obese workers compared to their counterparts. The likelihood of having hypertension among workers in the fields of installation, repair and maintenance, and production were 26% higher (APR, 1.26; 95% CI, 1.03–1.55) and 33% higher (APR, 1.33; 95% CI, 1.11–1.58), respectively, than workers in all other occupational groups. Among Mississippi workers, hypertension prevalence varied by sociodemographic characteristics and occupational groups. Age, race, obesity status, installation, repair, maintenance, and production occupation groups are associated with an increased likelihood of hypertension. Novel and/or community-based or linked programs are needed that could target workers at risk of hypertension that are outside of a single-site workplace.

1. Introduction

In 2017, Mississippi had the third highest age-adjusted prevalence (38.2%) of hypertension in the United States (US) [1]. Hypertension is a major risk factor for cardiovascular disease (CVD) and stroke [2]. In 2018, heart disease and stroke were the first and sixth leading causes of death in Mississippi, respectively [3]. Untreated or uncontrolled hypertension is the single largest contributor to CVD [4], which is the leading cause of death in Mississippi [5]. Work environment and work stress are associated with both ischemic heart disease [6] and coronary heart disease [7]. A prior epidemiological study has documented association between hypertension and occupation in US workers [8]. Data on hypertension and occupation among Mississippi workers are limited.

Understanding hypertension among the Mississippi workforce will facilitate the development of effective workplace promotion and intervention programs as well as work health related programs. We estimated the prevalence of hypertension by sociodemographic characteristics and occupation. Here, we report the estimation of the association between hypertension and occupation and sociodemographic characteristics among Mississippi workforce.

2. Methods

We analyzed combined data from the 2013, 2015, and 2017 Mississippi Behavioral Risk Factor Surveillance System (BRFSS), which included an industry and occupation module. The BRFSS is a state-based telephone survey of the U S noninstitutionalized civilian population aged 18 years or older. The survey was conducted in all 50 states, the District of Columbia, and the U S territories. Data from the BRFSS provide reliable and valid assessments of health risk factors [9] Detailed information about BRFSS is available at http://www.cdc.gov/brfss/. The Jackson State University Institutional Review Board deemed this study exempt from review.

Mississippi began collecting data via the optional industry and occupation module in 2012, but data on hypertension were only available in odd years. Survey respondents who were employed for wages or self-employed were asked, “What kind of business or industry do you work in?” and “What kind of work do you do?” Answers were open-ended and were coded using the 574 Census Bureau (2002) occupational numeric codes. For analysis, these codes were grouped into ten Standard Occupational Classification System major groups [10]. The current analyses were restricted to respondents who self-identified as black or white; which accounted for 96.6% of the Mississippi population in 2010 [3]. We excluded workers who were on active military duty (n = 26) as well as those missing information about employment (n = 852). The final analytic sample included 6,965 respondents.

High blood pressure was defined as a “yes” response to the question, “Have you ever been told by a doctor, nurse, or other health professional that you have high blood pressure?” Normal weight, overweight, and obesity were defined as having a body mass index (BMI) of 18.5–<25.0, 25.0–<30.0, and ≥30.0 kg/m2, respectively (calculated from self-reported height and weight).

2.1. Statistical Analyses

Adjusted prevalence and 95% confidence intervals (CIs) were calculated for hypertension prevalence overall and by sociodemographic characteristics and occupation, adjusting for age, sex, race, income, education, BMI, and occupation. In addition, logistic regression was used to calculate adjusted prevalence ratios (APRs) for hypertension in relation to sociodemographic characteristics and occupation. We used SAS 9.4 (SAS Institute, Inc.) and SUDAAN 11 to adjust for the disproportionate stratified sampling design of BRFSS; since 2011 a new statistical method called raking has been used to weight the BRFSS data. It included additional population characteristics such as educational level, marital status, and home ownership status of respondents [11]. We used a significance threshold of .

3. Results

There were an estimated 1,073,235 adult workers in Mississippi during the three survey years (2013, 2015, and 2017). Of these workers, 37.6% (95% CI, 36.0–39.3) were aged 30–44 years, 37.5% (95% CI, 36.0–39.0) were aged 45–64 years, 54.2% (95% CI, 52.6–55.8) were male, 37.5% (95% CI, 35.9–39.1) were black, 61.6% (95% CI, 60.1–63.4) had greater than a high school education, 40.2% (95% CI, 38.5–41.9) had an annual household income of less than $35,000, 36.2% (95% CI, 34.6–37.8) were classified as obese, and 22.8% (95% CI, 21.4–24.3) were current smokers (Table 1).


CharacteristicnaNb%C (95% CI)

Age group, years
18–2983225384624.9 (23.2–26.5)
30–44183238401037.6 (36.0–39.3)
45–64352238223637.5 (36.0–39.0)
Sex
Male309458191854.2 (52.6–55.8)
Female387149131745.8 (44.2–47.4)
Race
Black241540282137.5 (35.9–39.1)
White455167042162.5 (60.9–64.1)
Education level
<high school graduate44211240910.5 (9.3–11.7)
High school graduate or equivalent176729759127.8 (26.3–29.2)
>high school graduate474966232261.8 (60.1–63.4)
Annual household income, $
<35,000220638674240.2 (38.5–41.9)
35,000–49,99997214875915.5 (14.2–16.7)
≥50,000307742653244.3 (42.7–46.0)
Body mass index (kg/m2)
18.0–<25.0164426777926.8 (25.3–28.3)
25.0–<30.0243436973537.0 (35.4–38.6)
≥30240536170336.2 (34.6–37.8)
Current smoker
Yes123923449422.8 (21.4–24.3)
No547879213077.2 (75.7–78.6)

CI, conference interval; BRFSS, Behavioral Risk Factor Surveillance System. aUnweighted number. bWeighted number. cWeighted percentage.

The overall adjusted prevalence of hypertension among Mississippi workers was 31.4% (95% CI, 30.0–32.8). Men (32.3%; 95% CI, 30.2–34.4) had a higher adjusted prevalence than women (30.3%; 95% CI, 28.4–32.2). Adjusted prevalence of hypertension was higher in black workers (33.3%; 95% CI, 30.8–35.8) than white workers (30.2%; 95% CI, 28.5–32.0). Workers aged 45–64 years (47.5%; 95% CI, 45.4–49.7), those with less than a high school education (39.3%; 95% CI, 33.7–45.0), those with an annual household income of $35,000–$49,999 (34.1%; 95% CI, 30.1–38.1), and those with a BMI of ≥30.0 (44.4%; 95% CI, 41.8–47.1) had the highest adjusted prevalence of hypertension in their respective groups, and hypertension prevalence among current working smokers was 32.0% (95% CI, 28.7–35.4) (Table 1). Among the ten occupation categories, the following four occupation groups had the highest adjusted prevalence of hypertension: transportation and material moving (40.0%; 95% CI, 33.5–46.4); production (39.9%; 95% CI, 33.3–46.5); installation, repair, and maintenance (e.g., electric repairs, air-conditioning and heating system repairs, plumbing, painting, flooring, and mopping) (38.0%; 95% CI, 30.2–45.8); and management, business, and financial operations (37.4%; 95% CI, 32.8–42.0) (Table 2).


Occupational groupsAdjusted prevalence (%)a95% CI

Overall31.430.0–32.8
Age group, years
18–2911.08.5–13.6
30–4425.122.6–27.6
45–6447.545.4–49.7
Sex
Male32.330.2–34.4
Female30.328.4–32.2
Race
Black33.330.8–35.8
White30.228.5–32.0
Education level
<high school graduate39.333.7–45.0
High school graduate or equivalent31.628.9–34.2
>high school graduate30.028.2–31.7
Annual household income, $
<35,00031.228.7–33.7
35,000–49,99934.130.1–38.1
≥50,00031.829.6–33.9
Body mass index (kg/m2)
18.0–<25.016.214.0–18.4
25.0–<30.030.127.6–32.5
≥3044.441.8–47.1
Current smoker
Yes32.028.7–35.4
No68.064.6–71.3
Occupation group
Management, business, and financial operations37.432.8–42.0
Professional and related occupations29.326.6–32.1
Service occupations29.626.0–33.2
Sales and related29.524.6–34.3
Office and administrative support28.724.5–33.0
Construction and extraction24.118.2–30.0
Installation, repair, and maintenance38.030.2–45.8
Production39.933.3–46.5
Transportation and material moving40.033.5–46.4

CI, confidence interval; BRFSS, Behavioral Risk Factor Surveillance System. aAdjusted for age, sex, education, annual household income, body mass index, and smoking.

Relative to workers aged 18–29 years, the likelihood of hypertension among workers aged 30–44 years was 1.98 times higher (APR, 1.98; 95% CI, 1.46–2.68) and the likelihood among workers aged 45–64 years was 3.96 times higher (APR, 3.96; 95% CI, 2.97–5.28). The likelihood of hypertension was 19% higher (APR, 1.19; 95% CI, 1.06–1.33) among black workers than among white workers. Compared to workers with a normal weight, overweight workers had a 69% higher (APR, 1.69; 95% CI, 1.41–2.02) likelihood of hypertension while the likelihood of hypertension among obese workers was 2.56 times higher (APR, 2.56; 95% CI, 2.17–3.03). Compared to workers in all other occupations, installation, repair, and maintenance workers (automatic service technicians and mechanics; general maintenance and repair workers; heat, air-conditioning, and refrigeration mechanics and installers) had a 26% higher (APR, 1.26; 95% CI, 1.03–1.55) likelihood of hypertension, while workers in production (e.g., poultry, assemblers and fabricators, bakers, butchers and meat cutters, rigging, metal and plastic workers, and plant and system operators) had a 33% higher (APR, 1.33; 95% CI, 1.11–1.58) likelihood of hypertension (Table 3).


Occupational groupsAdjusted prevalence ratioa95% CI

Age group, years
18–29Reference
30–441.981.46–2.68
45–643.962.97–5.28
Sex
Male1.060.94–1.19
FemaleReference
Race
Black1.191.06–1.33
WhiteReference
Education level
<high school graduate1.140.93–1.40
High school graduate or equivalent0.950.84–1.08
>high school graduateReference
Annual household income
<35,0001.080.94–1.23
35,000–49,9991.140.98–1.32
≥50,000Reference
Body mass index (kg/m2)
18.0–<25.0Reference
25.0–<30.01.691.41–2.02
≥302.562.17–3.03
Current smoker
Yes1.100.98–1.25
NoReference
Occupation group
Management, business, and financial operations1.110.95–1.29
Professional and related occupations0.960.85–1.09
Service occupations0.910.79–1.06
Sales and related0.950.79–1.14
Office and administrative support0.930.78–1.10
Construction and extraction0.770.57–1.03
Installation, repair, and maintenance1.261.03–1.55
Production1.331.11–1.58
Transportation and material moving0.960.78–1.19
All other occupational groupsReference

CI, confidence interval; BRFSS, Behavioral Risk Factor Surveillance System. aAdjusted for age, sex, education, annual household income, body mass index, and smoking.

4. Discussion

An estimated 3 out of every 10 Mississippi workers had hypertension during the three survey years. Among the Mississippi work force, the prevalence of hypertension differed by occupation and sociodemographic characteristics. Age, race, and obesity status were associated with a higher prevalence of hypertension, as were specific occupational categories, such as installation, repair, maintenance, and production occupation groups.

The increased likelihood of having hypertension by age, race, and obesity status is consistent with previous research [12]. In addition, in the Jackson Heart Study cohort, mean systolic blood pressure and diastolic blood pressure levels increased with age [13], and obesity is associated increased incidence of hypertension [14]. The higher likelihood of hypertension among these subgroups may be partially due to an increasing proportion of Mississippi adults in the two highest-risk BMI categories (obesity, BMI ≥30; extreme obesity, BMI ≥40) [15] and a disproportionately higher prevalence of hypertension risk factors (e.g., physical inactivity and diabetes) among these groups [1]. In 2017, among Mississippi adults, diabetes prevalence was 13.3% for whites and 16.0% for blacks and 1.3% among those aged 18–24 years and 25.0% among those aged 55–64 years [16]. In addition, 31.6% of white adults reported not participating in any physical activity outside of work in the past 30 days compared to more than one-third (36.0%) among black adults.

The higher likelihood of hypertension among installation, repair, and maintenance workers could be due to occupational strain or stress [17] or long work hours [18]. In the Multiethnic Study of Atherosclerosis (MESA) study, among participants working more than 20 hours per week, Landsbergis et al., (2015) found that lower job decision latitude (“job control”) was associated with hypertension in several occupations [19]. In a prospective study of Canadian white collar workers, exposure to cumulative job strain had a modest but significant effect on systolic blood pressure among men. Those with low levels of social support at work had higher risk for increases in blood pressure [20]. A recent study also showed that long work hours increases blood pressure [21]. This could help explain our finding of increased likelihood of hypertension among Mississippi production workers. Production occupation exposure, including shiftwork and noise exposure, is shown to have additive effect of the occurrence of hypertension [22]. Employer-based workplace health promotion programs can lower the prevalence of chronic conditions such as hypertension and improve the health and well-being of workers [23].

BRFSS uniquely provides state-level estimates of occupation-specific hypertension prevalence among Mississippi adults. Because the BRFSS consists of self-reported information, the data are subject to recall bias and social desirability bias [24]. In addition, because the data are cross-sectional, we cannot make causal inferences based on the results.

5. Conclusion

Older adults, blacks, those classified as overweight and obese, and those in the fields of installation, repair and maintenance, and production could benefit from workplace prevention and health promotion programs focused on hypertension. There is a need for novel and/or community-based or linked programs that could target individuals at risk that are outside of a single-site workplace, potentially using mHealth and eHealth interventions and/or supporting the promotion of a medical home and/or regular visits with a healthcare provider to identify those at risk.

Data Availability

Data are available from the Mississippi State Department of Health for researchers who meet the criteria for data approval for research.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors would like to thank Nusrat Kabir of Jackson State University, School of Public Health, and Dr. Fleetwood Loustalot of the Division for Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention. The authors also thank the Program to Increase Diversity among Individuals Engaged in Cardiovascular Health-Related Research at SUNY Downstate Health Sciences University (subgrant no. 100-1091654-83591).

References

  1. Centers for Disease Control and Prevention, “National center for chronic disease prevention and health promotion, division of population health. BRFSS prevalence & trends data,” 2018, https://www.cdc.gov/brfss/brfssprevalence/. View at: Google Scholar
  2. E. J. Benjamin, P. Muntner, A. Alonso et al., “Heart disease and stroke statistics–2019 update: a report from the American heart association,” Circulation, vol. 139, no. 10, pp. e56–e528, 2019. View at: Publisher Site | Google Scholar
  3. Mississippi Vital Statistics, “The Mississippi statistically automated health resource system (MSTAHRS),” 2018, http://mstahrs.msdh.ms.gov/. View at: Google Scholar
  4. N. D. L. Fisher and G. Curfman, “Hypertension–a public health challenge of global proportions,” JAMA, vol. 320, no. 17, pp. 1757–1759, 2018. View at: Publisher Site | Google Scholar
  5. Centers for Disease Control and Prevention and National Center for Health Statistics, “Underlying cause of death 1999–2017 on CDC Wonder online database, released december, 2018. data are from the multiple cause of death files, 1999–2017, as compiled from data provided by the 57 vital statistics jurisdictions through the vital statistics cooperative program,” 2018, http://wonder.cdc.gov/ucd-icd10.html. View at: Google Scholar
  6. T. Theorell, K. Jood, L. S. Järvholm et al., “A systematic review of studies in the contributions of the work environment to ischaemic heart disease development,” The European Journal of Public Health, vol. 26, no. 3, pp. 470–477, 2016. View at: Publisher Site | Google Scholar
  7. T. Chandola, A. Britton, E. Brunner et al., “Work stress and coronary heart disease: what are the mechanisms?” European Heart Journal, vol. 29, no. 5, pp. 640–648, 2008. View at: Publisher Site | Google Scholar
  8. E. P. Davila, E. V. Kuklina, A. L. Valderrama, P. W. Yoon, I. Rolle, and P. Nsubuga, “Prevalence, management, and control of hypertension among U. S workers,” Journal of Occupational and Environmental Medicine, vol. 54, no. 9, pp. 1150–1156, 2012. View at: Publisher Site | Google Scholar
  9. C. Pierannunzi, S. S. Hu, and L. Balluz, “A systematic review of publications assessing reliability and validity of the behavioral risk factor surveillance system (BRFSS), 2004–2011,” BMC Medical Research Methodology, vol. 13, no. 1, p. 49, 2013. View at: Publisher Site | Google Scholar
  10. T. M. Shockey, A. L. Sussell, and E. C. Odom, “Cardiovascular health status by occupational group–21 states, 2013,” MMWR. Morbidity and Mortality Weekly Report, vol. 65, no. 31, pp. 793–798, 2016. View at: Publisher Site | Google Scholar
  11. R. Iachan, C. Pierannunzi, K. Healey, K. J. Greenlund, and M. Town, “National weighting of data from the behavioral risk factor surveillance system (BRFSS),” BMC Medical Research Methodology, vol. 16, no. 1, p. 155, 2016. View at: Publisher Site | Google Scholar
  12. D. B. Vinholes, S. L. Bassanesi, H. C. Chaves junior et al., “Association of workplace and population characteristics with prevalence of hypertension among Brazilian industry workers: a multilevel analysis,” BMJ Open, vol. 7, no. 8, Article ID e015755, 2017. View at: Publisher Site | Google Scholar
  13. S. B. Wyatt, E. L. Akylbekova, M. R. Wofford et al., “Prevalence, awareness, treatment, and control of hypertension in the Jackson heart study,” Hypertension, vol. 51, no. 3, pp. 650–656, 2008. View at: Publisher Site | Google Scholar
  14. H. M. Shihab, L. A. Meoni, A. Y. Chu et al., “Body mass index and risk of incident hypertension over the life course,” Circulation, vol. 126, no. 25, pp. 2983–2989, 2012. View at: Publisher Site | Google Scholar
  15. V. L. Mendy, R. Vargas, M. Payton, and G. Cannon-Smith, “Association between consumption of sugar-sweetened beverages and sociodemographic characteristics among Mississippi adults,” Preventing Chronic Disease, vol. 14, p. E4, 2017. View at: Publisher Site | Google Scholar
  16. The Mississippi behavioral surviellance sytem, 2017, https://msdh.ms.gov/msdhsite/_static/31,0,110.html.
  17. T. Rosenthal and A. Alter, “Occupational stress and hypertension,” Journal of the American Society of Hypertension, vol. 6, no. 1, pp. 2–22, 2012. View at: Publisher Site | Google Scholar
  18. H. Yang, P. L. Schnall, M. Jauregui, T.-C. Su, and D. Baker, “Work hours and self-reported hypertension among working people in California,” Hypertension, vol. 48, no. 4, pp. 744–750, 2006. View at: Publisher Site | Google Scholar
  19. P. A. Landsbergis, A. V. Diez-roux, K. Fujishiro et al., “Job strain, occupational category, systolic blood pressure, and hypertension prevalence,” Journal of Occupational and Environmental Medicine, vol. 57, no. 11, pp. 1178–1184, 2015. View at: Publisher Site | Google Scholar
  20. C. Guimont, C. Brisson, G. R. Dagenais et al., “Effects of job strain on blood pressure: a prospective study of male and female white-collar workers,” American Journal of Public Health, vol. 96, no. 8, pp. 1436–1443, 2006. View at: Publisher Site | Google Scholar
  21. X. Trudel, C. Brisson, M. Gilbert-ouimet, M. Vézina, D. Talbot, and A. Milot, “Long working hours and the prevalence of masked and sustained hypertension,” Hypertension, vol. 75, no. 2, pp. 532–538, 2020. View at: Publisher Site | Google Scholar
  22. M. Attarchi, F. Dehghan, F. Safakhah, M. Nojomi, and S. Mohammadi, “Effect of exposure to occupational noise and shift working on blood pressure in rubber manufacturing company workers,” Industrial Health, vol. 50, no. 3, pp. 205–213, 2012. View at: Publisher Site | Google Scholar
  23. L. S. Fischer, J. E. Lang, R. Z. Goetzel, L. A. Linnan, and P. G. Thorpe, “CDC grand rounds: new frontiers in workplace health,” MMWR. Morbidity and Mortality Weekly Report, vol. 67, no. 41, pp. 1156–1159, 2018. View at: Publisher Site | Google Scholar
  24. A. Althubaiti, “Information bias in health research: definition, pitfalls, and adjustment methods,” Journal of Multidisciplinary Healthcare, vol. 9, pp. 211–217, 2016. View at: Publisher Site | Google Scholar

Copyright © 2020 Vincent L. Mendy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views440
Downloads251
Citations

Related articles

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.