Health-Related Quality of Life Among US Veterans and Civilians by Race and Ethnicity
Cecily Luncheon, MD, DrPH; Matthew Zack, MD, MPH
Suggested citation for this article: Luncheon C, Zack M. Health-Related Quality of Life Among US Veterans and Civilians by Race and Ethnicity. Prev Chronic Dis 2012;9:110138. DOI: http://dx.doi.org/10.5888/pcd9.110138.
Among veterans, having been selected into the military and having easy access to medical care during and after military service may reduce premature mortality but not morbidity from mental distress and may not improve health-related quality of life. The objective of this study was to determine whether veterans in different racial/ethnic groups differ in their health-related quality of life from each other and from their civilian counterparts.
Among 800,000 respondents to the 2007–2009 Behavioral Risk Factor Surveillance System surveys, approximately 110,000 identified themselves as veterans and answered questions about their sociodemographic characteristics, self-rated health, and recent health-related quality of life. Nonoverlapping 95% confidence intervals of means distinguished veterans and civilians of different racial/ethnic groups.
Veteran and civilian American Indians/Alaska Natives reported more physically unhealthy days, mentally unhealthy days, and recent activity limitation days than their veteran and civilian counterparts in other racial/ethnic groups. Non-Hispanic white veterans and Hispanic veterans reported more physically unhealthy days, mentally unhealthy days, and recent activity limitation days than their civilian counterparts.
Unlike findings in other studies, our findings show that veterans’ health-related quality of life differs from that of civilians both within the same racial/ethnic group and among different racial/ethnic groups. Because once-healthy soldiers may not be as healthy when they return to civilian life, assessing their health-related quality of life over time may identify those who need help to regain their health.
Each soldier’s experience in the military is unique, whether the soldier volunteered or was drafted into military service (1). After being selected, completing basic training, and going off to their assignments, all soldiers have the common experience that they are generally healthier than those excluded from military service (2). Preliminary screening disqualifies those who are less physically and psychologically fit, remaining in the service requires meeting physical and psychological standards, and accessing medical care is easier during and after military service. This “healthy soldier” effect may reduce premature mortality among soldiers compared with their nonsoldier peers even after military service has ended.
This benefit of reduced premature mortality for soldiers may not carry over to reduced morbidity from mental distress and improved health-related quality of life (HRQOL) (3-5). Overall quality of life involves individual and subjective evaluations of the positive and negative aspects of life based on one’s values and culture and includes who one is (part of a family, health, function), what one does (cares for others, works, goes to school), and where one lives (community, nation) (6). HRQOL is that part of overall quality of life that affects physical and mental health (7,8). HRQOL includes a person’s perceptions of his or her physical and mental health, which results from health risks, conditions, functional status, socioeconomic status, and social support. For example, HRQOL in the general US population varies by sociodemographic characteristics including race/ethnicity, risky behaviors, reported chronic health conditions, activity limitation, and social support (9-19).
Previous studies have examined the HRQOL of veterans with mixed results (20-23). Some studies compared HRQOL among active duty, reserve, and veteran military personnel with that of those with no military service without directly analyzing HRQOL by race/ethnicity (20-22). Another study compared scores on the Medical Outcomes Study Short Form 36-item Survey for Veterans for active duty and Reserve/National Guard military personnel by race/ethnicity to US normative scale scores (23). However, none of these studies has analyzed racial/ethnic differences in HRQOL of representative samples of veterans and their nonveteran civilian counterparts. The objective of this study was to determine whether veterans in different racial/ethnic groups differ in their HRQOL from each other (primary) and from their civilian counterparts (secondary).
This study is a descriptive analysis of cross-sectional data from respondents to the 2007–2009 surveys of the Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS is an annual random-digit–dialed telephone survey in all 50 US states, the District of Columbia, Puerto Rico, the Virgin Islands, and the US Pacific territories (24). Eligible participants are adults (1 per household) aged 18 years or older interviewed about their health status, access to health care, and health behaviors. The Centers for Disease Control and Prevention (CDC) institutional review board has reviewed and approved the BRFSS protocol. The BRFSS method, design, questionnaires, and data sets are available in the public domain (24).
Of 1,278,028 participants in the 2007–2009 BRFSS, 801,862 (63%) answered a question about their status as a veteran (see definition below) and identified themselves as either non-Hispanic whites, non-Hispanic blacks, American Indians/Alaska Natives, or Hispanics. Twelve percent (n = 110,365) of these reported being a veteran, 100,829 (92%) men and 9,536 (8%) women (values are weighted). We compared veterans and their civilian counterparts within racial/ethnic groups by age, marital status, educational level, employment status, annual income, and HRQOL.
The HRQOL items used for this study were self-rated health (excellent, very good, good, fair, or poor), physically unhealthy days (the number of days during the past 30 days when one’s physical health was not good), mentally unhealthy days (the number of days during the past 30 days when one’s mental health was not good), and recent activity limitation days (the number of days during the past 30 days when one’s physical or mental health kept one from doing one’s usual activities). The question about veteran status remained the same during the 2007–2009 BRFSS surveys: “Have you ever served on active duty in the United States Armed Forces, either in the regular military or in a National Guard or military reserve unit? Active duty does not include training for the Reserves or National Guard, but DOES include activation, for example, for the Persian Gulf War.” However, the response choices differed in the 2009 questionnaires from those in the 2008 and 2007 questionnaires. In 2009, participants chose from 7 responses: 1) yes, now on active duty; 2) yes, on active duty during the last 12 months, but not now; 3) yes, on active duty in the past, but not during the last 12 months; 4) no, training for Reserves or National Guard only; 5) no, never served in the military; 6) don’t know/not sure; and 7) refused. In the 2007 and 2008 BRFSS, there were 4 choices: yes, no, don’t know/not sure, and refused. For this study, we defined veterans as those answering yes to these questions on any of the 3 surveys and civilians as those answering no to these questions. We excluded from the analysis those answering don’t know/not sure and those refusing to answer these questions.
The demographic characteristics analyzed were the following: race/ethnicity (non-Hispanic white, non-Hispanic black, American Indian/Alaska Native, or Hispanic); age group (18–24, 25–34, 35–44, 45–54, 55–64, or ≥65 y), marital status (currently married or not), educational level (≤high school, attended college or technical school, or graduated from college or technical school), employment status (currently employed for wages or self-employed, not currently employed [includes the unemployed, students, homemakers, or unable to work], or retired), and annual household income (<$15,000, $15,000–$24,999, $25,000–$34,999, $35,000–$49,999, or ≥$50,000).
To account for the BRFSS complex sample design and sampling weights, we used SAS-callable SUDAAN version 9.2 (RTI International, Research Triangle Park, North Carolina) to estimate demographic characteristics and self-rated health and mean unhealthy days by veteran status and race/ethnicity, both unadjusted and adjusted for sex, age group, marital status, educational level, employment status, and annual household income. Nonoverlapping 95% confidence intervals of means statistically distinguished veterans and civilians of different racial/ethnic groups.
Women were more likely than men to be civilians, although non-Hispanic black and Hispanic women were more likely than non-Hispanic white women to be veterans (Table 1). Hispanic veterans usually reported their health as being better than that of their civilian counterparts, non-Hispanic blacks and American Indian/Alaska Native veterans as about the same, and non-Hispanic white veterans as being worse; non-Hispanic white civilians generally reported their health as better than that of civilians in other racial/ethnic groups.
American Indian/Alaska Native veterans reported more physically unhealthy days and recent activity limitation days than veterans in other racial/ethnic groups (Table 2). American Indian/Alaska Native civilians said they had more physically unhealthy days, mentally unhealthy days, and recent activity limitation days than civilians in other racial/ethnic groups. American Indian/Alaska Native veterans and non-Hispanic white veterans described themselves as having more physically unhealthy days and non-Hispanic white veterans reported more recent activity limitation days than their civilian counterparts. Non-Hispanic white and black veterans reported fewer mentally unhealthy days than their civilian counterparts.
After adjusting for sex, age, marital status, educational level, employment status, and annual household income, American Indian/Alaska Native veterans still reported more physically unhealthy days and recent activity limitation days than veterans in other racial/ethnic groups (Table 2). American Indian/Alaska Native civilians still said they had more physically unhealthy days, mentally unhealthy days, and recent activity limitation days than civilians in other racial/ethnic groups. Veterans in all racial/ethnic groups reported more physically unhealthy days than their civilian counterparts, but only non-Hispanic white and Hispanic veterans said they had more mentally unhealthy days and recent activity limitation days than their civilian counterparts.
This study explored differences in the associations between the HRQOL of veterans and civilians by racial/ethnic group. Despite the “healthy soldier” effect, other studies have documented poorer mental and physical health in some veterans, which might be expected to affect their health perceptions or HRQOL (3-5,25-27). Yet, in none of these studies was race or ethnicity associated with poorer mental and physical health after accounting for other potentially confounding variables. In this study, however, the HRQOL of veterans differed from that of their civilian counterparts both within the same racial/ethnic group and among different racial/ethnic groups. What happened to these veterans during or after military service may have affected these differences in their current HRQOL. The higher number of mean physically unhealthy days among veterans of all racial/ethnic groups compared with that of their civilian counterparts, even after adjustment, may indicate persistent effects of physical trauma associated with military service (28). Veterans who belonged to racial/ethnic groups that may be discriminated against more often, American Indians/Alaska Natives and non-Hispanic blacks, did not differ from their civilian counterparts with respect to their mental or activity-limiting HRQOL, perhaps because discrimination against these groups after military service affects these aspects of HRQOL more than military service alone (29,30). However, veterans who belong to racial/ethnic groups that may be less discriminated against, non-Hispanic whites and Hispanics, still reported worse mental and activity-limiting HRQOL than their civilian counterparts, suggesting that military service can affect these aspects of HRQOL.
Compared with these other studies, our study had several strengths. It analyzed HRQOL in different racial/ethnic groups and had sizable numbers of respondents in these groups, allowing for the adjustment of potentially confounding sociodemographic characteristics. The BRFSS questions on HRQOL have acceptable validity and reliability (7,9). Because these HRQOL questions preceded those asking about veterans status, the ascertainment of status as a veteran probably did not affect responses about HRQOL.
This study also had several limitations. Because BRFSS depends on self-reported experiences, we could not corroborate reports of veteran status, although respondents would not benefit from falsely reporting themselves as veterans or denying they were veterans. Moreover, HRQOL is inherently subjective, and we could not corroborate differences in HRQOL with objective indicators of health and functional status (eg, physician records of diagnosed disease, hospitalizations) that affect HRQOL. Because the questions in the 2007–2009 BRFSS do not distinguish between participation in the military and exposure to combat and do not ask about duration of military service (www.cdc.gov/brfss/), we could not tell whether exposure to combat and duration of military service affected the observed differences in HRQOL among the different racial/ethnic groups of veterans. Moreover, because BRFSS is cross-sectional, we could not tell whether the observed differences in HRQOL between veterans and civilians occurred because of events during military service or afterward. The small number of women veterans in some racial/ethnic groups precluded comparison of their HRQOL with that of their civilian counterparts. Until recently, BRFSS has been based on landline residential telephones and excludes US adults who use only cell phones and whose sociodemographic characteristics and responses to BRFSS may differ from those who use landline residential telephones.
The HRQOL differences in this study between veterans and their civilian counterparts and among veterans in different racial/ethnic groups may indicate persistent health problems associated with military service, persistent discrimination against certain racial/ethnic groups despite their military service, or both. Because once-healthy soldiers may not be as healthy when they return to civilian life, assessing their HRQOL over time may identify those who need help to regain their health.
This project was supported in part by appointment to the Research Participation Program for CDC administered by the Oak Ridge Institute for Science and Education through an agreement between the Department of Energy and CDC. This research received no specific grant from any funding agency in the public, commercial, or nonprofit sectors.
Corresponding Author: Matthew Zack, MD, MPH, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, MS K-51, Atlanta, GA 30341. Telephone: 770-488-5460. E-mail: Matthew.Zack@cdc.hhs.gov.
Author Affiliations: Cecily Luncheon, Centers for Disease Control and Prevention, Atlanta, Georgia.
- Levy BS, Sidel VW. Health effects of combat: a life-course perspective. Annu Rev Public Health 2009;30:123-36. CrossRef PubMed
- McLaughlin R, Nielsen L, Waller M. An evaluation of the effect of military service on mortality: quantifying the healthy soldier effect. Ann Epidemiol 2008;18(12):928-36. CrossRef PubMed
- Hoge CW, Auchterlonie JL, Milliken CS. Mental health problems, use of mental health services, and attrition from military service after returning from deployment to Iraq or Afghanistan. JAMA 2006;295(9):1023-32. CrossRef PubMed
- Sareen J, Cox BJ, Afifi TO, Stein MB, Belik SL, Meadows G, et al. Combat and peacekeeping operations in relation to prevalence of mental disorders and perceived need for mental health care: findings from a large representative sample of military personnel. Arch Gen Psychiatry 2007;64(7):843-52. CrossRef PubMed
- Vasterling JJ, Proctor SP, Amoroso P, Kane R, Heeren T, White RF. Neuropsychological outcomes of army personnel following deployment to the Iraq war. JAMA 2006;296(5):519-29. CrossRef PubMed
- The World Health Organization Quality of Life Assessment (WHOQOL): development and psychometric properties. Soc Sci Med 1998;46(12):1569-85. PubMed
- Measuring healthy days: population assessment of health-related quality of life. Centers for Disease Control and Prevention; 2000. http://www.cdc.gov/hrqol/pdfs/mhd.pdf. Accessed February 6, 2011.
- McHorney CA. Health status assessment methods for adults: past accomplishments and future challenges. Annu Rev Public Health 1999;20:309-35. CrossRef PubMed
- Zahran HS, Kobau R, Moriarty DG, Zack MM, Holt J, Donehoo R, et al. Health-related quality of life surveillance — United States, 1993-2002. MMWR Surveill Summ 2005;54(4):1-35. PubMed
- Mody RR, Smith MJ. Smoking status and health-related quality of life: as findings from the 2001 Behavioral Risk Factor Surveillance System data. Am J Health Promot 2006;20(4):251-8. CrossRef PubMed
- Okoro CA, Brewer RD, Naimi TS, Moriarty DG, Giles WH, Mokdad AH. Binge drinking and health-related quality of life: do popular perceptions match reality? Am J Prev Med 2004;26(3):230-3. CrossRef PubMed
- Brown DW, Balluz LS, Heath GW, Moriarty DH, Ford ES, Giles WH, et al. Associations between recommended levels of physical activity and health-related quality of life — findings from the 2001 Behavioral Risk Factor Surveillance System (BRFSS) survey. Prev Med 2003;37(5):520-8. CrossRef PubMed
- Ford ES, Moriarty DG, Zack MM, Mokdad AH, Chapman DP. Self-reported body mass index and health-related quality of life: findings from the Behavioral Risk Factor Surveillance System. Obes Res 2001;9(1):21-31. CrossRef PubMed
- Mili F, Helmick CG, Moriarty DG. Health-related quality of life among adults reporting arthritis: analysis of data from the Behavioral Risk Factor Surveillance System, US, 1996-99. J Rheumatol 2003;30(1):160-6. PubMed
- Ford ES, Mokdad AH, Li C, McGuire LC, Strine TW, Okoro CA, et al. Gender differences in coronary heart disease and health-related quality of life: findings from 10 states from the 2004 Behavioral Risk Factor Surveillance System. J Womens Health (Larchmt) 2008;17(5):757-68. CrossRef PubMed
- Kobau R, Zahran H, Grant D, Thurman DJ, Price PH, Zack MM. Prevalence of active epilepsy and health-related quality of life among adults with self-reported epilepsy in California: California Health Interview Survey, 2003. Epilepsia 2007;48(10):1904-13. CrossRef PubMed
- Campbell VA, Crews JE, Moriarty DG, Zack MM, Blackman DK. Surveillance for sensory impairment, activity limitation, and health-related quality of life among older adults — United States, 1993-1997. MMWR CDC Surveill Summ 1999;48(8):131-56. PubMed
- Strine TW, Chapman DP, Kobau R, Balluz L, Mokdad AH. Depression, anxiety, and physical impairments and quality of life in the U.S. noninstitutionalized population. Psychiatr Serv 2004;55(12):1408-13. CrossRef PubMed
- Strine TW, Chapman DP, Balluz L, Mokdad AH. Health-related quality of life and health behaviors by social and emotional support. Their relevance to psychiatry and medicine. Soc Psychiatry Psychiatr Epidemiol 2008;43(2):151-9. CrossRef PubMed
- Barrett DH, Boehmer TK, Boothe VL, Flanders WD, Barrett DH. Health-related quality of life of U.S. military personnel: a population-based study. Mil Med 2003;168(11):941-7. PubMed
- Centers for Disease Control and Prevention. Behavioral risk factors among U.S. Air Force active-duty personnel, 1995. MMWR Morb Mortal Wkly Rep 1998;47(28):593-6. PubMed
- Kazis LE, Miller DR, Clark J, Skinner K, Lee A, Rogers W, et al. Health-related quality of life in patients served by the Department of Veterans Affairs: results from the Veterans Health Study. Arch Intern Med 1998;158(6):626-32. CrossRef PubMed
- Smith TC, Zamorski M, Smith B, Riddle JR, Leardmann CA, Wells TS, et al. The physical and mental health of a large military cohort: baseline functional health status of the Millennium Cohort. BMC Public Health 2007;7:340. CrossRef PubMed
- Behavioral Risk Factor Surveillance System. Turning information into health. http://www.cdc.gov/brfss/index.htm. Accessed April 10, 2011.
- Baker DG, Heppner P, Afari N, Nunnink S, Kilmer M, Simmons A, et al. Trauma exposure, branch of service, and physical injury in relation to mental health among U.S. veterans returning from Iraq and Afghanistan. Mil Med 2009;174(8):773-8. PubMed
- Hankin CS, Spiro A, Miller DR, Kazis L. Mental disorders and mental health treatment among U.S. Department of Veterans Affairs outpatients: the Veterans Health Study. Am J Psychiatry 1999;156(12):1924-30. PubMed
- West A, Weeks WB. Physical and mental health and access to care among nonmetropolitan Veterans Health Administration patients younger than 65 years. J Rural Health 2006;22(1):9-16. CrossRef PubMed
- Barrett DH, Doebbeling CC, Schwartz DA, Voelker MD, Falter KH, Woolson RF, Doebbeling BN. Posttraumatic stress disorder and self-reported physical health status among U.S. military personnel serving during the Gulf War period: a population-based study. Psychosomatics 2002;43(3):195-205. CrossRef PubMed
- Helms JE, Nicolas G, Green CE. Racism and ethnoviolence as trauma: enhancing professional training. Traumatology 2010;16(4):53-62. CrossRef
- Alim TN, Charney DS, Mellman TA. An overview of posttraumatic stress disorder in African Americans. J Clin Psychol 2006;62(7):801-13. CrossRef PubMed
Table 1. Characteristics of Veterans and Civilians by Race/Ethnicity, Behavioral Risk Factor Surveillance System, 2007–2009a
|Characteristics||Veterans (n = 110,365)||Civilians (n = 691,497)|
|Non-Hispanic White||Non-Hispanic Black||American Indian/ Alaska Native||Hispanic||Non-Hispanic White||Non-Hispanic Black||American Indian/ Alaska Native||Hispanic|
|% (95% CI)|
|Female||7 (6-8)||12 (11–14)||9 (6-13)||10 (8-13)||59 (58–60)||60 (59–62)||54 (51–57)||52 (50–53)|
|Age group, y|
|18–24||2 (1-3)||3 (2-5)||4 (1-9)||6 (4-9)||11 (10–12)||14 (13–16)||19 (16–23)||19 (17–20)|
|25–34||7 (6-8)||12 (10–15)||8 (4-14)||18 (15–22)||17 (17–18)||21 (20–22)||20 (18–23)||27 (26–28)|
|35–44||12 (11–13)||23 (20–26)||15 (11–20)||18 (15–21)||20 (19–20)||21 (20–22)||19 (17–21)||23 (22–24)|
|45–54||14 (13–14)||23 (20–25)||19 (15–24)||16 (14–19)||21 (20–22)||19 (17–20)||19 (17–21)||15 (14–16)|
|55–64||24 (23–25)||19 (17–21)||27 (22–32)||17 (15–20)||15 (14–15)||13 (12–14)||13 (11–14)||9 (8-10)|
|≥65||41 (40–42)||20 (18–22)||27 (22–33)||25 (22–28)||16 (16–17)||12 (11–13)||10 (9-12)||8 (7-9)|
|Married||75 (74–76)||59 (57–62)||61 (54–67)||69 (65–72)||63 (62–64)||37 (36–39)||47 (44–50)||54 (52–55)|
|High school diploma or less||34 (33–35)||35 (32–37)||38 (33–44)||35 (31–38)||36 (35–36)||49 (48–50)||55 (53–58)||64 (63–65)|
|Some college or technical school||30 (29–31)||38 (35–40)||34 (28–40)||37 (33–40)||27 (26–28)||27 (26–29)||27 (24–30)||20 (19–21)|
|Graduated from college or technical school||37 (35–38)||28 (25–30)||28 (22–34)||29 (25–32)||38 (37–38)||24 (23–25)||18 (16–20)||16 (15–17)|
|Employed||49 (48–50)||57 (55–60)||49 (43–55)||60 (56–63)||63 (62–63)||58 (56–59)||55 (52–57)||61 (59–62)|
|Not employed||9 (8-10)||18 (15–20)||17 (13–22)||14 (11–17)||22 (22–23)||30 (29–32)||35 (32–37)||33 (32–35)|
|Retired||42 (41–43)||25 (23–27)||34 (29–40)||27 (24–30)||15 (14–16)||12 (11–13)||11 (9-12)||6 (5-7)|
|Annual household income, $|
|<15,000||5 (4-5)||9 (7-11)||13 (9-17)||10 (8-13)||7 (6-7)||17 (16–18)||18 (15–21)||22 (21–23)|
|15,000–24,999||13 (12–14)||15 (13–17)||19 (14–24)||15 (12–18)||12 (11–13)||23 (22–24)||24 (21–26)||28 (26–29)|
|25,000–34,999||12 (11–13)||13 (11–15)||16 (11–21)||12 (10–15)||10 (9-11)||15 (14–16)||14 (12–16)||15 (13–16)|
|35,000–49,999||18 (17–19)||20 (18–23)||17 (12–22)||17 (14–20)||15 (14–15)||15 (14–16)||15 (12–17)||13 (12–14)|
|≥50,000||53 (52–54)||43 (40–46)||36 (30–43)||46 (42–50)||57 (56–57)||30 (29–32)||30 (28–33)||22 (21–24)|
|Excellent||18 (17–19)||18 (16–21)||16 (12–21)||22 (19–26)||22 (22–23)||17 (16–18)||17 (15–20)||17 (15–18)|
|Very good||32 (31–33)||27 (24–29)||23 (18–28)||28 (24–31)||37 (36–38)||26 (25–28)||25 (22–28)||20 (19–22)|
|Good||31 (30–32)||34 (31–36)||34 (28–40)||30 (27–33)||28 (27–29)||36 (34–37)||34 (31–37)||37 (35–38)|
|Fair||13 (12–14)||15 (13–17)||15 (11–19)||14 (12–17)||9 (9-10)||16 (14–17)||15 (13–17)||22 (20–23)|
|Poor||6 (5-7)||6 (4-8)||13 (9-17)||6 (5-9)||4 (3-4)||6 (5-6)||9 (7-10)||5 (4-6)|
Table 2. Unadjusteda and Adjustedb Mean Unhealthy Days for Veterans and Civilians by Race/Ethnicity, Behavioral Risk Factor Surveillance System, 2007–2009
|Measure||Non-Hispanic White||Non-Hispanic Black||American Indian/Alaska Native||Hispanic|
|Mean (95% CI)|
|Physically unhealthy days|
|Unadjusted||4.2 (4.1–4.4)||3.4 (3.4–3.5)||4.4 (3.9–4.9)||3.9 (3.7–4.0)||7.3 (5.9–8.6)||5.3 (4.9–5.7)||4.2 (3.6–4.7)||3.6 (3.5–3.8)|
|Adjusted||4.1 (3.9–4.2)||3.7 (3.6–3.8)||4.0 (3.5-4.5)||3.2 (3.0–3.3)||6.7 (5.3–8.1)||4.7 (4.2–5.1)||4.1 (3.5–4.7)||2.8 (2.6–3.0)|
|Mentally unhealthy days|
|Unadjusted||2.6 (2.4–2.7)||3.4 (3.3–3.5)||3.3 (2.9–3.7)||4.0 (3.8–4.1)||3.8 (2.9–4.7)||5.1 (4.7–5.6)||3.0 (2.6–3.4)||3.6 (3.4–3.7)|
|Adjusted||4.0 (3.8–4.1)||3.6 (3.5–3.7)||3.6 (3.2–4.1)||3.1 (2.9–3.3)||4.2 (3.3–5.1)||4.3 (3.8–4.7)||3.7 (3.2–4.2)||2.4 (2.2–2.6)|
|Recent activity limitation days|
|Unadjusted||2.5 (2.4–2.6)||2.1 (2.0–2.2)||2.9 (2.4–3.3)||2.6 (2.4–2.7)||4.7 (3.6–5.8)||3.9 (3.5–4.3)||2.6 (2.1–3.1)||2.1 (2.0–2.3)|
|Adjusted||2.6 (2.5–2.8)||2.3 (2.2–2.4)||2.6 (2.1–3.0)||2.0 (1.8–2.1)||4.4 (3.2–5.5)||3.3 (2.9–3.7)||2.6 (2.1–3.1)||1.4 (1.2–1.5)|
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