- Email: [email protected]
Gender Differences in Pain Risk in Old Age: Magnitude and Contributors
ORIGINAL ARTICLE
Gender Differences in Pain Risk in Old Age: Magnitude and Contributors Esther García-Esquinas, MD; Isabel Rodríguez-Sánchez, MD; Rosario Ortolá, PhD; Esther Lopez-Garcia, PhD; Francisco Félix Caballero, PhD; Leocadio Rodríguez-Mañas, MD; José R. Banegas, MD; and Fernando Rodríguez-Artalejo, MD Abstract Objectives: To identify the factors associated with the excess risk of pain observed among older women compared with men. Patients and Methods: We used information from a cohort of 851 women and men age 63 years and older who were free of pain during 2012 and were followed up to December 31, 2015. Sociodemographic variables, health behaviors, psychosocial factors, morbidity, and functional limitations were assessed in 2012 during home visits. Incident pain in 2015 was classified according to its frequency, intensity, and number of localizations into lowest, middle, and highest categories. Results: During a mean follow-up of 2.8 years, the incidence of middle and highest pain was 12.5% and 22.6% in women and 12.4% and 12.6% in men, respectively. The age-adjusted relative risk ratios and 95% CIs of middle and highest pain in women versus men were 1.20 (0.79-1.83) and 2.03 (1.40-2.94), respectively. In a mediation analysis, a higher frequency in women than men of osteomuscular disease, impaired mobility, and impaired agility accounted, respectively, for 31.1%, 46.6%, and 32.0% of the excess risk of highest pain in women compared with men. Other relevant mediators were psychological distress (25.2%), depression (8.7%), poor sleep quality (10.7%), and lower recreational physical activity (12.6%). Conclusion: A greater frequency of some chronic diseases, worse functional status, psychological distress, and lower physical activity can mediate the excess risk of pain in older women compared with men. Trial Registration: clinicaltrials.gov Identifier: NCT02804672 ª 2019 Mayo Foundation for Medical Education and Research
C
hronic pain is a growing public health concern, particularly among older adults. Approximately 20% of the population has chronic pain,1 defined as pain on most days or every day for the past 6 months.2 The prevalence of chronic pain increases with age; thus, it affects up to 60% of people older than 65 years.3-6 Moreover, chronic pain has a major influence on the health of older people because it leads to reduced physical activity7 and increases the risk of the frailty syndrome,8,9 falls,10,11 physical disability,12 and cognitive impairment.13 As a result, chronic pain is the leading cause of years lived with disability in people age 50 years and older.14,15
n
Mayo Clin Proc. 2019;94(9):1707-1717
The health burden of chronic pain is greater in older women than men14,15 because in most population-based studies, the frequency and intensity of pain is also higher in women.1,4-6 Compared with men, women usually have a lower pain threshold and lower pain tolerance, and they experience greater unpleasantness (or intensity) with pain.16 However, in many cases of chronic pain, no specific cause is identified (most people have “primary” pain),17,18 so the reasons for the excess pain in women versus men are not well known. A better understanding of these reasons may serve to lower the incidence of pain in older women and, subsequently, to reduce the gender
Mayo Clin Proc. n September 2019;94(9):1707-1717 n https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org n ª 2019 Mayo Foundation for Medical Education and Research
For Limelight, see page 1655 From the Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/ IdiPaz, Spain (E.G-E., I.R-S., R.O., E.L-G., F.F.C., J.R.B., F.R-A.); Centro de Investigación Biomédica en Red of Epidemiology and Public Health, Madrid, Spain (E.G-E., R.O., E.L-G., F.F.C., J.R.B., F.R-A.); Department Affiliations continued at the end of this article.
1707
MAYO CLINIC PROCEEDINGS
2008-2009 n=3289 95 deaths 675 losses to follow-up 2012 n=2519 95 deaths 600 losses to follow-up 2015 n=1824 Exclusion criteria: 103 with no information on pain in 2012 or 2015 759 with pain at baseline 94 with no information on diet and alcohol consumption 17 with no information in other potential confounders
FIGURE. Flow of participants in the Seniors-Estudio de Nutrición y Riesgo Cardiovascular en España cohort.
difference in pain and its health burden. Therefore, we conducted a mediation analysis of a cohort of older women and men in Spain to identify health behaviors and psychosocial and clinical factors that are associated with the excess risk of pain among female compared with male participants. PATIENTS AND METHODS Study Design and Participants We analyzed data from the Seniors-Estudio de Nutrición y Riesgo Cardiovascular en España cohort, whose methods has been reported elsewhere.19,20 This population-based cohort included community-dwelling individuals age 60 years and older and selected during 2008-2018 in Spain. Data were collected in 3 stages. First, a telephone interview was used to obtain sociodemographic variables, health behaviors, morbidity, and health services use. Next, 2 home visits were conducted to collect questionnaire-based information, perform a physical examination, obtain a diet history, and collect biological samples. Data were gathered by trained and certified staff members from January 1, 2012, through December 31, 2015. Information was updated 1708
Mayo Clin Proc.
n
in 2012 (wave 1) and 2015 (wave 2). Given that information on pain was first obtained in 2012, analyses for this study were conducted with the 1824 participants in 2012 who were followed up to 2015. From these individuals, we excluded those with chronic pain at baseline or incomplete data on pain and risk factors for pain in 2012 or 2015; thus, analyses were performed with 851 people (Figure). Study participants gave informed written consent. The study was approved by the Ethics Research Committee of La Paz University Hospital in Madrid. Study Variables Pain. Pain was reported using 10 items from the questionnaire used in the Survey on Chronic Pain in Europe.4 Participants reporting pain at least 2 times per week in the last 6 months were classified as suffering persistent pain; those reporting pain 1 time per week, 1-3 times per month or less than 1 time per month were deemed to have sporadic pain; and those without pain in the past 6 months were classified as having no pain. Because analyses were performed among individuals free of pain at baseline, pain variables described later provide information on pain characteristics at follow-up. Impact of pain on habitual activities of daily living was used to assess pain intensity. Participants with pain troubling them moderately, a lot, or completely were deemed to have moderate- to high-intensity pain; those with little trouble had light intensity pain; and those with no trouble had very-low-intensity pain. Participants classified as having high-, light-, and very-lowintensity incident pain reported an average intensity of 8.1, 5.0, and 2.4 points (in a scale from 1 [no pain] through 10 [a pain I cannot even imagine bearing]), respectively. Individuals reported pain in 6 localizations: (1) head and neck, (2) back, (3) bones and joints, (4) legs, (5) arms, and (6) other sites. This scale was used to classify them according to the number of pain sites: 0, 1-2, and 3. We built a pain scale based on frequency of pain, its intensity, and the number of sites. Given that we assigned a score of 1 and 2,
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
respectively, to sporadic and persistent pain, to light and moderate-high intensity, and to 1-2 and 3 or more sites, the scale ranged from 0 to 6 (worst pain). This scale serves to classify participants into 3 groups: lowest pain (0 points), middle pain (1-4 points), and highest pain (5-6 points). The cutoff point between middle and highest pain was the median score in those with a pain score of 1-6.21 Potential Mediators of the Association Between Sex and Incident Pain. Potential mediators have been selected because they were associated with pain risk in the literature16,22,23 and may have an unequal distribution in women and men. These variables were measured in 2012 and include the following. Sociodemographic Factors. Sociodemographic factors were age and level of education (primary, secondary, university). Health Behaviors. Health behaviors included tobacco and alcohol consumption, diet quality, sedentary behavior, physical activity, and body mass index (BMI). Self-reported tobacco smoking was classified as never-, former-, and current-smoking. Consumption of beverages and food was ascertained with a validated computerized diet history.24 This tool collected information on 34 alcoholic beverages, and alcohol intake was estimated using standard composition tables. Diet quality was represented by adherence to the Mediterranean diet, as summarized with the Mediterranean Diet Adherence Screener (MEDAS) score, which consists of 14 items with targets for food consumption and habits characteristic of this diet in Spain. MEDAS score ranges from 0 to 14, and a higher score indicates better adherence to the Mediterranean diet.25 For the present analyses, we excluded the alcohol component of the index (included above considered as a separate behavior), so that the modified score ranged from 0 to 13. Sedentary behavior was approximated by time spent watching television, obtained with the Nurses’ Health Study Questionnaire.26 Recreational and Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
household physical activity was derived from the European Prospective Investigation into Cancer and Nutrition cohort questionnaire and expressed in metabolic equivalents taskehours per week.27 Lastly, weight and height were measured with standardized procedures,19 and BMI was calculated as kilograms per square meter. BMI was categorized as normal weight (19.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obesity (30 kg/m2). Psychosocial Factors. Psychosocial factors included social network, housing conditions, sleep quality, and psychological distress. Social network was assessed with a questionnaire regarding marital status (yes, no), cohabitation (yes, no), daily contact with family (yes, no) and friends (yes, no), being alone at home less than 2 h/d (yes, no), and being usually accompanied while walking away from home (yes, no). We built a social network scale by assigning 1 point to each affirmative response, resulting in a range of 0-6 (greatest network).28 Individuals reported their housing conditions, which we summarized as feeling (or not feeling) cold at home.29 Participants were asked to report their quality of sleep as “very poor”, “poor”, “fair” (categorized as poor sleep), “good”, or “very good” (categorized as good sleep).30 Psychological distress was assessed with the 12-item General Health Questionnaire; it ranges from 0 to 12, with higher scores indicating greater short-term distress.31 Morbidity. Individuals reported the following physician-diagnosed diseases: cardiovascular disease (ischemic heart disease, stroke, or heart failure), chronic obstructive lung disease, diabetes, osteomuscular disease (osteoarthritis, arthritis or hip fracture), and depression requiring treatment.19 Functional Limitations. We assessed limitations in agility and mobility with the Rosow scale32 and in instrumental activities of daily living (IADL) with the Lawton-Brody index.33 Impaired agility was defined as answering “a lot” to the following question: “On an average day with your current
https://doi.org/10.1016/j.mayocp.2019.03.034
1709
MAYO CLINIC PROCEEDINGS
health, would you be limited in bending and kneeling?” The categories of response were “yes, a lot,” “yes, a little,” and “not at all.” Likewise, impaired mobility was defined as answering “a lot” to any of the three corresponding questions on (1) picking up or carrying a shopping bag, (2) climbing one flight of stairs, and (3) walking several city blocks (a few hundred meters). The LawtonBrody index evaluates independent complex living skills, including the individual’s ability to go shopping, use the telephone, prepare meals, do housework, do laundry, use different means of transportation, take medication, and manage finances. Because of cultural issues, questions about preparation of meals, housework, and laundry were not asked in men; therefore, the scale ranged 0-8 points in women and 0-5 in men. In the present analyses, a higher score indicates worse function. Finally, we also performed the Mini-Mental State Examination,34 which assesses cognitive function. The Mini-Mental State Examination scale ranges from 0 to 30 (highest functioning). Statistical Analyses Analyses were performed in 4 subsequent stages. First, we estimated the risk of middle and highest pain during follow-up in women and men; gender differences in pain risk were summarized with age-adjusted relative risk ratios (RRRs) obtained from multinomial (pain in 3 categories) logistic regression, using men as reference category (model 1). Second, we also used multinomial logistic regression to assess the association between the potential mediators at baseline and the risk of pain during followup in the total study sample. Moreover, we checked that the associations were consistent in men and women. Results are presented as age- and sex-adjusted RRR and their 95% CI. Third, we assessed gender differences in the baseline prevalence of the potential mediators of the study association. Fourth, we estimated the contribution of each potential mediator to gender differences in pain risk. To this end, we built a logistic model (model 2) in which we added each potential mediator (each at a time) to model 1710
Mayo Clin Proc.
n
1. Next, we compared the gender-associated RRR of pain risk in model 1 versus model 2. The percentage reduction in the RRR in model 2 versus 1 ([RRR2 e RRR1] 100) / (RRR1-1) corresponds to the magnitude of the mediation by each factor.35,36 Of note is that only those variables that had somewhat unequal frequency in women and men, and that showed an association with pain risk, can mediate the difference in pain risk between women and men. Statistical significance was set at 2-sided P<.05. Statistical analyses were performed with STATA (version 14.0; Stata Corp., College Station, TX).
RESULTS During a mean follow-up of 2.8 years, the incidence of middle and highest pain in women was 12.5% and 22.6%, respectively. Corresponding figures for men were 12.4% and 12.6%. Accordingly, the age-adjusted RRR of middle and highest pain in women versus men was 1.20 (95% CI, 0.79-1.83) and 2.03 (95% CI, 1.40.-2.94), respectively. Excess risk of highest pain in women resulted from an excess risk of persistent pain (RRR, 1.78; 95% CI, 1.26-2.53), moderate- to high-intensity pain (RRR, 1.92; 95% CI, 1.33-2.77), and pain at 3 or more sites (RRR, 2.45; 95% CI, 1.59-3.78) in women. The excess risk of pain in women was observed as statistically significant only for the highest pain category. Table 1 shows the association between the potential mediators at baseline and the risk of highest versus lowest pain during follow-up. Being older, overweight, or obese; having a stronger social network, poor sleep quality, or psychological distress; suffering from cardiovascular disease, chronic lung disease, or osteomuscular disease; and having limitations in agility, mobility, and IADL were all associated with increased risk of highest pain. In contrast, more physical household activity was associated with reduced risk. In addition, individuals suffering from depression or diabetes showed a nonstatistically significant increased risk of highest pain, whereas those who engaged in more
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
TABLE 1. Relative risk ratios (95% CI) for incident highest pain in 2015, according to sociodemographic factors, health behaviors, psychosocial factors, and clinical characteristics in 2012 among older adults (n ¼ 851) Highest vs. lowest pain, RRRa (95% CI)
Characteristics Sociodemographic factors
1.04 (1.00-1.07)b
Age (years) Educational level Secondary vs Primary
0.85 (0.54-1.35)
University vs Primary
1.16 (0.73-1.84)
Health behaviors Tobacco smoking Former smoker vs never smoker
1.20 (0.76-1.91)
Current smoker vs never smoker
1.02 (0.50-2.07)
Alcohol intake, gm/d
1.00 (0.98-1.01)
Mediterranean diet (MEDAS)
1.07 (0.95-1.20)
Watching TV, h/wk
1.01 (0.99-1.03)
Recreational physical activity (MET-h/wk)
0.99 (0.97-1.00)
Second vs first tertile
0.93 (0.60-1.46)
Third vs first tertile
0.76 (0.48-1.19)
Household physical activity (MET-h/wk) Second vs first tertile
0.83 (0.54-1.27)
Third vs first tertile
0.47 (0.29-0.75)b
Body mass index, kg/m2 25-29.9 vs <25
1.74 (1.06-2.86)b
30 vs <25
2.22 (1.31-3.75)b
Psychosocial factors Social network score
1.24 (1.03-1.48)b
Feeling cold at home
1.53 (0.72-3.27)
Poor sleep quality
2.24 (1.49-3.37)b
GHQ-12 sore
1.18 (1.09-1.27)b
Morbidity Cardiovascular diseasec
2.10 (1.16-3.82)b
Diabetes
1.27 (0.82-1.98) 2.09 (1.18-3.66)b
d
Chronic lung disease
Osteomuscular disease
2.64 (1.77-3.94)b
Depression
1.48 (0.84-2.59)
e
Functional limitations 3.05 (2.04-4.56)b
Agility impairment
3.14 (2.09-4.70)b
Mobility impairment Limitation in IADL
2.07 (1.22-3.53)b
Mini-Mental State Examination
1.05 (0.94-1.18)
f
GHQ-12 ¼ 12-item General Health Questionnaire; IADL ¼ instrumental activities of daily living; MEDAS ¼ Mediterranean Diet Adherence Screener (excluding alcohol); MET ¼ metabolic equivalents task; RRR ¼ relative risk ratio. b P<.05. Statistically significant results in boldface. c Ischemic heart disease, stroke, and heart failure. d Asthma or chronic bronchitis. e Osteoarthritis, arthritis, and hip fracture. f In the present analyses, a higher score in the Lawton and Brody Score indicates worse function. a
Relative risk ratios (RRR) were adjusted for age and sex in 2012 (when age was the studied mediator, adjustment was only made for sex).
Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
https://doi.org/10.1016/j.mayocp.2019.03.034
1711
MAYO CLINIC PROCEEDINGS
TABLE 2. Sociodemographic factors, health behaviors, psychosocial factors, and clinical characteristics of study participants with no pain in 2012, by sex (N ¼ 785) Men (n ¼ 484)
Women (n ¼ 367)
P value
71.3 (5.9)
72.1 (5.8)
.06
Primary
37.4
55.9
Secondary
31.2
25.3
University
31.4
18.8
Never smoker
26.6
78.2
Former smoker
59.1
17.2
Current smoker
14.3
4.6
<.01
15.7 (16.5)
3.9 (7.7)
<.01
Characteristics Sociodemographic factors Mean age, years (SD) Education level, %
<.01
Health behaviors Tobacco smoking, %
Mean alcohol intake, gm/d (SD) Mean MEDASa score (SD)
6.4 (1.5)
6.2 (1.6)
<.01
Mean time watching television, h/wk (SD)
16.9 (9.4)
19.5 (9.7)
<.01
Mean recreational activity, MET-h/wk (SD)
26.7 (16.8)
19.9 (11.7)
11.8 (6.0)
8.3 (4.8)
Second tertile
25.2 (3.8)
19.0 (2.3)
Third tertile
45.7 (13.2)
33.3 (7.5)
2.5 (2.4)
21.9 (10.6)
First tertile
<.01
Mean household activity, MET-h/wk (SD) First tertile Second tertile
14.5 (4.6)
44.7 (7.2)
Third tertile
39.2 (14.2)
80.1 (18.2)
20.7
33.2
25-29.9 kg/m
50.2
42.0
30 kg/m2
29.1
24.8
<.01
3.6 (0.9)
3.6 (1.2)
.19
4.6
5.5
.55
<.01
Body mass index, % <25 kg/m2 2
Psychosocial factors Mean social network score (SD) Feeling cold at home, %
18.2
26.4
<.01
0.7 (1.6)
1.5 (2.5)
<.01
Cardiovascular disease,b %
8.1
7.4
.71 <.01
Poor sleep quality, % Mean GHQ-12 score (SD) Morbidity Diabetes, %
25.6
15.3
Chronic lung disease,c %
7.0
10.9
.04
Osteomuscular disease,d %
38.0
58.6
<.01
Depression, %
4.8
16.1
<.01
Functional limitations Agility impairment, %
35.3
54.5
<.01
Mobility impairment, %
16.1
39.8
<.01 Continued on next page
1712
Mayo Clin Proc.
n
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
TABLE 2. Continued Men (n ¼ 484)
Characteristics
Women (n ¼ 367)
P value
Functional limitations, continued Limitation in IADL,e %
0.03 (0.2)
0.06 (0.4)
.12
Mini-Mental State Examination, mean (SD)
28.8 (1.4)
28.1 (2.0)
<.01
GHQ-12 ¼ 12-item General Health Questionnaire; IADL ¼ instrumental activities of daily living; MEDAS ¼ Mediterranean Diet Adherence Screener (excluding alcohol); MET ¼metabolic equivalents task. b Ischemic heart disease, stroke and heart failure. c Asthma or chronic bronchitis. d Osteoarthritis, arthritis, and hip fracture. e In the present analyses, a higher score in the Lawton and Brody Score indicates worse function. a
Differences were tested with an analysis of variance (ANOVA) or the chi-square test for continuous and categorical variables, respectively.
recreational physical activity had a nonsignificant reduced risk. Among the factors associated with increased risk of highest pain, chronic lung disease, osteomuscular disease, depression, poor sleep quality, and limitations in agility and mobility were more frequent in women than in men (Table 2). Compared with men, women also performed less recreational activity and had a worse score on the 12-item General Health Questionnaire. Therefore, these factors can mediate the excess risk of highest pain in women compared with men, because they are risk factors of pain (independently of sex; Table 1) and have a higher prevalence in women (Table 2). Table 3 shows the magnitude of their mediation. Specifically, osteomuscular disease, impaired mobility, and impaired agility were the largest mediating factors for the excess risk of pain in women versus men, because they accounted, respectively, for 31.1%, 46.6%, and 32.0% of the excess risk. Other relevant mediators were psychological distress (25.2%), depression (8.7%), poor sleep quality (10.7%), and lower recreational physical activity (12.6%). Of note is that some risk factors for highest pain, including excess weight, cardiovascular disease, and diabetes, were less frequent in women than in men (Table 2). Therefore, the magnitude of the excess risk of pain in women compared with men would have been even larger (15.5%, 3.90%, and 5.9%, respectively) had the prevalence of each of these factors been the same in each Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
gender (Table 3). Lastly, household activity, a protective factor for highest pain, was greater in women (Table 2). Accordingly, the excess risk of pain in women would have been 70.9% higher if women had done the same household activity as men (Table 3). DISCUSSION In this study among community-living older people in Spain, women showed a greater risk of highest pain than men did. This excess risk was partly explained by more frequent osteomuscular disease and worse physical function status in women than in men. Other mediating factors were worse mental health, particularly greater psychological distress, and lower physical activity. Our results are consistent with previous literature indicating that pain risk is higher in older women than in men.1,4-6 However, excess risk in women was limited to the most severe forms of pain, including a higher number of localizations and impact on daily activities, possibly because, compared with men, women experience greater unpleasantness with pain, suffer more comorbid pain conditions, and are more likely to develop disability from the same pain condition.16 Our results on risk factors for pain are mostly in line with previous research. Previous investigations also found that low physical activity,37-39 excess weight,40,41 poor sleep quality,42 chronic diseases43 (osteomuscular disease,43-45 cardiovascular disease,43 chronic lung disease,46,47
https://doi.org/10.1016/j.mayocp.2019.03.034
1713
MAYO CLINIC PROCEEDINGS
TABLE 3. Relative risk ratios (95% CI) for incident highest pain in women versus men, with adjustment for potential mediators, and percentage change in relative risk ratios of model 1 after additional adjustment for such potential mediators RRRa (95% CI)
Characteristics
Percentage of change in RRR
Adjusted for age (model 1)
2.03 (1.40-2.94)
d
Model 1 additionally adjusted for educational level
2.05 (1.41-3.00)
e1.9
Model 1 and tobacco
2.21 (1.42-3.42)
e17.5
Model 1 and alcohol
1.95 (1.30-2.93)
7.8
Model 1 and MEDAS
2.06 (1.42-2.99)
e2.9
Model 1 and watching television
2.00 (1.37-2.90)
2.9
Model 1 and recreational physical activity
1.90 (1.30-2.77)
12.6
Model 1 and household physical activity
2.76 (1.77-4.31)
e70.9
Model 1 and BMI (normal weight, overweight, obesity)
2.19 (1.50-3.19)
e15.5
Model 1 and social network
2.07 (1.43-3.00)
e3.9
Model 1 and feeling cold at home
2.02 (1.40-2.93)
1.0
Model 1 additionally adjusted for health behaviors
Model 1 additionally adjusted for psychosocial factors
Model 1 and sleep quality
1.92 (1.32-2.79)
10.7
Model 1 and GHQ-12
1.77 (1.22-2.61)
25.2
Model 1 and cardiovascular disease
2.07 (1.42-3.00)
e3.9
Model 1 and diabetes
2.09 (1.44-3.04)
e5.9
Model 1 and chronic lung disease
1.98 (1.37-2.88)
4.9
Model 1 and osteomuscular disease
1.71 (1.17-2.50)
31.1
Model 1 and depression
1.94 (1.33-2.83)
8.7
Model 1 additionally adjusted for morbidity
Model 1 additionally adjusted for functional limitations
a
Model 1 and agility impairment
1.70 (1.16-2.48)
32.0
Model 1 and mobility impairment
1.55 (1.05-2.29)
46.6
Model 1 and limitation in IADL
2.00 (1.37-2.90)
2.9
Model 1 and Mini-mental State Examination
2.10 (1.44-3.05)
e6.8
BMI ¼ body mass index; IADL ¼ instrumental activities of daily living; GHQ-12 ¼ 12-item General Health Questionnaire; MEDAS ¼ Mediterranean Diet Adherence Screener (excluding alcohol); RRR ¼ relative risk ratio.
diabetes,48,49 anxiety and depression43,50), and limitations in physical function51 are associated with increased risk of pain. All these health behaviors, morbid conditions, and functional impairments show bidirectional associations and can be part of the same altered health complex. For example, low physical activity can lead to excess weight, and both of them increase the risk of sleep problems and chronic diseases, and vice versa. In addition, low activity and excess weight can lead to functional impairments, usually mediated by chronic diseases. Finally, anxiety and depression frequently coexist with, and compound, many of these 1714
Mayo Clin Proc.
n
conditions. In fact, multimorbidity is a strong pain risk factor,43 and pain in one location increases the risk of pain in other sites.21,22,43 The distribution of risk factors of pain in men and women in our study is similar to that in the older general population of Spain. In the 2017 National Health Survey of Spain, conducted on a representative sample of the noninstitutionalized Spanish population, older women also showed lower recreational physical activity, less frequent excess weight, more psychological distress, and higher prevalence of osteomuscular disease, depression, and limitations in mobility and IADL
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
than their age-matched male counterparts did.52 This finding suggests that our results on the mediators of excess risk of pain in older women compared with men could be applied to the older Spanish population. In most developed countries, the sex distribution of the variables is in line with that observed in our study, but the relative importance of each mediator can vary according to the between-gender difference in its prevalence in each country. We are not aware of any previous study that comprehensively assessed a good number of potential mediators of differences in pain risk between men and women. Our study extends knowledge in this field by showing that certain health behaviors (eg, low recreational activity) and conditions (eg, osteomuscular disease, psychological distress, depression, poor sleep quality, and functional impairment), which are frequently clustered, can partly explain the excess risk of highest pain in women. Moreover, our results are clinically relevant because they suggest that improving physical function and psychological health and increasing physical activity (both recreational and at household) can be a starting point to lower pain risk in older women and reduce the gender gap in pain. In fact, there is evidence that physical activity can reduce pain onset and intensity, improve sleep quality and mood, lower the risk of chronic disease, and reduce functional limitations.37-39,53 However, future research should confirm our results in other populations and test the effectiveness of female-focused population and clinical interventions to promote physical activity and to prevent age-related declines in physical and psychological health to reduce the pain burden. Our study has several strengths and limitations. Among the former is the prospective study design, which reinforces causal inference regarding the observed risk factors of pain. In addition, the fact that the identified pain risk factors and their gender distribution were consistent with literature adds credibility to our study results. Regarding the limitations, perhaps the main one was the lack of data on many biologic mediators, Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
including genetic and omic factors and hormonal status; therefore, we could not assess their contribution to pain differences between women and men nor their interaction with the studied behavioral, psychosocial, and clinical factors. In addition, the pain questionnaire has not been validated, and we did not collect information on the type of pain (eg, neuropathic, nociceptive) and its etiology. However, we used items similar to other widely used questionnaires. In a previous article,23 we showed that the distribution of pain categories across sociodemographics, lifestyle, and chronic diseases was consistent with the literature.4-6 Lastly, morbidity was self-reported, which might underestimate its prevalence, particularly for their milder forms; however, about half of the older women and men in our study visited the primary care practitioner at least once per month,20 which limits underdiagnosis and differential diagnosis between women and men.
CONCLUSION This study suggests that a greater frequency of some chronic diseases and worse functional status as well as a lower physical activity can mediate the excess risk of pain in older women versus men. Future research should assess the role of sex-related biologic factors and their interaction with the above mediators in explaining differences in pain risk between older men and women. Moreover, it should test whether interventions aiming to increase physical activity may lower the women-associated pain burden. Abbreviations and Acronyms: BMI = body mass index; IADL = Instrumental Activities of Daily Living; MEDAS = Mediterranean Diet Adherence Screener; RRR = relative risk ratio Affiliations (Continued from the first page of this article.): of Geriatric Medicine, Hospital Universitario La Paz/ IdiPaz, Madrid, Spain (I.R-S.); and Department of Geriatric Medicine, Hospital Universitario de Getafe and CIBER of Frailty and Healthy Ageing, Getafe, Spain (L.R-M.). Grant Support: This work was supported by FIS grants 16/ 609, 16/1512, and 18/0028 (Instituto de Salud Carlos III, State Secretary of R þ D þ I, and FEDER/FSE), the
https://doi.org/10.1016/j.mayocp.2019.03.034
1715
MAYO CLINIC PROCEEDINGS
ATHLOS project (EU H2020-Project ID: 635316), and the JPI HDHL (SALAMANDER project). 17.
Potential Competing Interests: The authors report no competing interests. Correspondence: Address to Esther García-Esquinas, MD, Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo 4, 28029 Madrid, Spain ([email protected]).
REFERENCES
19.
20.
21.
1. Dahlhamer J, Lucas J, Zelaya C, et al. Prevalence of chronic pain and high-impact chronic pain among adults - United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(36):1001-1006. 2. International Association for the Study of Pain. Classification of chronic pain, second edition (revised). Available at: https://www. iasp-pain.org/PublicationsNews/Content.aspx?ItemNumber¼ 1673&navItemNumber¼677. Accessed October 25, 2018. 3. Fayaz A, Croft P, Langford RM, Donaldson LJ, Jones GT. Prevalence of chronic pain in the UK: a systematic review and meta-analysis of population studies. BMJ Open. 2016;6(6): e010364. 4. Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain. 2006;10(4):287-333. 5. Miró J, Paredes S, Rull M, et al. Pain in older adults: a prevalence study in the Mediterranean region of Catalonia. Eur J Pain. 2007; 11(1):83-92. 6. Gálvez-Barrón C, Narvaiza L, Dapena MD, Macho O, Rodríguez-Molinero A. Prevalence and treatment of pain in noninstitutionalized very old population: transversal study at national level. Aging Clin Exp Res. 2016;28(2):347-353. 7. Stubbs B, Binnekade TT, Soundy A, Schofield P, Huijnen IP, Eggermont LH. Are older adults with chronic musculoskeletal pain less active than older adults without pain? A systematic review and meta-analysis. Pain Med. 2013;14(9):1316-1331. 8. Veronese N, Maggi S, Trevisan C, et al. Pain increases the risk of developing frailty in older adults with osteoarthritis. Pain Med. 2017;18(3):414-447. 9. Bindawas SM, Vennu V, Stubbs B. Longitudinal relationship between knee pain status and incident frailty: data from the Osteoarthritis Initiative. Pain Med. 2018;19(11):2146-2152. 10. Leveille SG, Jones RN, Kiely DK, et al. Chronic musculoskeletal pain and the occurrence of falls in an older population. JAMA. 2009;302(2):2214-2221. 11. Stubbs B, Schofield P, Binnekade T, Patchay S, Sepehry A, Eggermont L. Pain is associated with recurrent falls in community-dwelling older adults: evidence from a systematic review and meta-analysis. Pain Med. 2014;15(7):1115-1128. 12. Andrews JS, Cenzer IS, Yelin E, Covinsky KE. Pain as a risk factor for disability or death. J Am Geriatr Soc. 2013;61(4):583-589. 13. Moriarty O, McGuire BE, Finn DP. The effect of pain on cognitive function: a review of clinical and preclinical research. Prog Neurobiol. 2011;93(3):385-404. 14. Buchbinder R, van Tulder M, Öberg B, et al. Lancet Low Back Pain Series Working Group. Low back pain: a call for action. Lancet. 2018;391(10137):2384-2388. 15. Institute for Health Metrics and Evaluation. Global Burden of Disease Compare. Data visualization. Available at: https:// vizhub.healthdata.org/gbd-compare/ 2016. Accessed October 25, 2018. 16. Greenspan JD, Craft RM, LeResche L, et al; Consensus Working Group of the Sex, Gender, and Pain SIG of the IASP. Studying
1716
18.
Mayo Clin Proc.
n
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32. 33.
34.
35.
sex and gender differences in pain and analgesia: a consensus report. Pain. 2007;132(suppl 1):S26-S45. Treede RD, Rief W, Barke A, et al. A classification of chronic pain for ICD-11. Pain. 2015;156(6):1003-1007. Mills S, Torrance N, Smith BH. Identification and management of chronic pain in primary care: a review. Curr Psychiatry Rep. 2016;18(2):22. Rodríguez-Artalejo F, Graciani A, Guallar-Castillón P, et al. Rationale and methods of the Study on Nutrition and Cardiovascular Risk in Spain (ENRICA). Rev Esp Cardiol. 2011;64(10): 876-882. Hernández-Aceituno A, Pérez-Tasigchana RF, GuallarCastillón P, López-García E, Rodríguez-Artalejo F, Banegas JR. Combined healthy behaviors and healthcare services use in older adults. Am J Prev Med. 2017;53(6):872-881. van Hecke O, Torrance N, Smith BH. Chronic pain epidemiology - where do lifestyle factors fit in? Br J Pain. 2013;7(4): 209-217. Hartvigsen J, Hancock MJ, Kongsted A, et al. Lancet Low Back Pain Series Working Group. What low back pain is and why we need to pay attention. Lancet. 2018;391(10137):2356-2367. Rodríguez-Sánchez I, García-Esquinas E, Mesas AE, MartínMoreno JM, Rodríguez-Mañas L, Rodríguez-Artalejo F. Frequency, intensity and localization of pain as risk factors for frailty in older adults. Age Ageing. 2019;48(1):74-80. Guallar-Castillón P, Sagardui-Villamor J, Balboa-Castillo T, et al. Validity and reproducibility of a Spanish dietary history. PLoS One. 2014;9(1):e86074. Schröder H, Fitó M, Estruch R, et al. A short screener is valid for assessing Mediterranean diet adherence among older Spanish men and women. J Nutr. 2011;141(6):1140-1145. Martínez-Gonzalez MA, López-Fontana C, Varo JJ, SánchezVillegas A, Martínez JA. Validation of the Spanish version of the physical activity questionnaire used in the Nurses’ Health Study and the Health Professionals’ Follow-up Study. Public Health Nutr. 2005;8(7):920-927. Pols MA, Peeters PH, Ocke MC, Slimani N, Bueno-deMesquita HB, Collette HJ. Estimation of reproducibility and relative validity of the questions included in the EPIC Physical Activity Questionnaire. Int J Epidemiol. 1997;26(suppl 1): S181-S189. Sánchez-Martínez M, López-García E, Guallar-Castillón P, et al. Social support and ambulatory blood pressure in older people. J Hypertens. 2016;34(10):2045-2052. García-Esquinas E, Pérez-Hernández B, Guallar-Castillón P, Banegas JR, Ayuso-Mateos JL, Rodríguez-Artalejo F. Housing conditions and limitations in physical function among older adults. J Epidemiol Community Health. 2016;70(10):954-960. Campanini MZ, Guallar-Castillón P, Rodríguez-Artalejo F, Lopez-Garcia E. Mediterranean diet and changes in sleep duration and indicators of sleep quality in older adults. Sleep. 2017;40(3). Sánchez-López MP, Dresch V. The 12-Item General Health Questionnaire (GHQ-12): Reliability, external validity and factor structure in the Spanish population. Psicothema. 2008; 20(4):839-843. Rosow I, Breslau N. A Guttman health scale for the aged. J Gerontol. 1966;21(4):556-559. Lawton MP, Brody EM. Assessment of older people: selfmaintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179-186. Escribano-Aparicio M, Pérez-Dively M, García-García F, et al. Validación del MMSE de Folstein en una población española de bajo nivel educativo. Rev Esp Geriatr Gerontol. 1999;34(6): 319-326. Wamala SP, Wolk A, Orth-Gomér K. Determinants of obesity in relation to socioeconomic status among middle-aged Swedish women. Prev Med. 1997;26(5 Pt 1):734-744.
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
36. MacKinnon DP, Krull JL, Lockwood CM. Equivalence of the mediation, confounding and suppression effect. Prev Sci. 2000; 1(4):173-181. 37. Landmark T, Romundstad P, Borchgrevink PC, Kaasa S, Dale O. Associations between recreational exercise and chronic pain in the general population: evidence from the HUNT 3 study. Pain. 2011;152(10):2241-2247. 38. Paley CA, Johnson MI. Physical activity to reduce systemic inflammation associated with chronic pain and obesity: a narrative review. Clin J Pain. 2016;32(4):365-370. 39. Shiri R, Falah-Hassani K. Does leisure time physical activity protect against low back pain? Systematic review and meta-analysis of 36 prospective cohort studies. Br J Sports Med. 2017;51(19): 1410-1418. 40. Okifuji A, Hare BD. The association between chronic pain and obesity. J Pain Res. 2015;8:399-408. 41. Zhang TT, Liu Z, Liu YL, Zhao JJ, Liu DW, Tian QB. Obesity as a risk factor for low back pain: a meta-analysis. Clin Spine Surg. 2018;31(1):22-27. 42. Finan PH, Goodin BR, Smith MT. The association of sleep and pain: an update and a path forward. J Pain. 2013;14(12):15391552. 43. Dominick CH, Blyth FM, Nicholas MK. Unpacking the burden: understanding the relationships between chronic pain and comorbidity in the general population. Pain. 2012; 153(2):293-304. 44. van Dijk GM, Dekker J, Veenhof C, van den Ende CH; Carpa Study Group. Course of functional status and pain in osteoarthritis of the hip or knee: a systematic review of the literature. Arthritis Rheum. 2006;55(5):779-785.
Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
45. Bastick AN, Verkleij SP, Damen J, et al. Defining hip pain trajectories in early symptomatic hip osteoarthritis–5 year results from a nationwide prospective cohort study (CHECK). Osteoarthritis Cartilage. 2016;24(5):768-775. 46. Lee AL, Harrison SL, Goldstein RS, Brooks D. Pain and its clinical associations in individuals with COPD: a systematic review. Chest. 2015;147(5):1246-1258. 47. Christensen VL, Holm AM, Kongerud J, et al. Occurrence, characteristics, and predictors of pain in patients with chronic obstructive pulmonary disease. Pain Manag Nurs. 2016;17(2):107-118. 48. Ferreira PH1, Beckenkamp P, Maher CG, Hopper JL, Ferreira ML. Nature or nurture in low back pain? Results of a systematic review of studies based on twin samples. Eur J Pain. 2013;17(7):957-971. 49. Pai LW, Hung CT, Li SF, Chen LL, Chung Y, Liu HL. Musculoskeletal pain in people with and without type 2 diabetes in Taiwan: a population-based, retrospective cohort study. BMC Musculoskelet Disord. 2015;16:364. 50. Woo AK. Depression and anxiety in pain. Rev Pain. 2010;4(1): 8-12. 51. Thapa S, Shmerling RH, Bean JF, Cai Y, Leveille SG. Chronic multisite pain: evaluation of a new geriatric syndrome [published online ahead of print October 25 2018]. Aging Clin Exp Res, https://doi.org/10.1007/s40520-018-1061-3. 52. Ministerio de Sanidad, Consumo y Bienestar Social. Encuesta Nacional de Salud de España 2017. Available at: https://www. mscbs.gob.es/en/estadEstudios/estadisticas/encuestaNacional/ encuesta2017.htm. Accessed November 2, 2018. 53. The 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Available at: https://health.gov/paguidelines/ second-edition/report.aspx. Accessed November 2, 2018.
https://doi.org/10.1016/j.mayocp.2019.03.034
1717
Gender Differences in Pain Risk in Old Age: Magnitude and Contributors Esther García-Esquinas, MD; Isabel Rodríguez-Sánchez, MD; Rosario Ortolá, PhD; Esther Lopez-Garcia, PhD; Francisco Félix Caballero, PhD; Leocadio Rodríguez-Mañas, MD; José R. Banegas, MD; and Fernando Rodríguez-Artalejo, MD Abstract Objectives: To identify the factors associated with the excess risk of pain observed among older women compared with men. Patients and Methods: We used information from a cohort of 851 women and men age 63 years and older who were free of pain during 2012 and were followed up to December 31, 2015. Sociodemographic variables, health behaviors, psychosocial factors, morbidity, and functional limitations were assessed in 2012 during home visits. Incident pain in 2015 was classified according to its frequency, intensity, and number of localizations into lowest, middle, and highest categories. Results: During a mean follow-up of 2.8 years, the incidence of middle and highest pain was 12.5% and 22.6% in women and 12.4% and 12.6% in men, respectively. The age-adjusted relative risk ratios and 95% CIs of middle and highest pain in women versus men were 1.20 (0.79-1.83) and 2.03 (1.40-2.94), respectively. In a mediation analysis, a higher frequency in women than men of osteomuscular disease, impaired mobility, and impaired agility accounted, respectively, for 31.1%, 46.6%, and 32.0% of the excess risk of highest pain in women compared with men. Other relevant mediators were psychological distress (25.2%), depression (8.7%), poor sleep quality (10.7%), and lower recreational physical activity (12.6%). Conclusion: A greater frequency of some chronic diseases, worse functional status, psychological distress, and lower physical activity can mediate the excess risk of pain in older women compared with men. Trial Registration: clinicaltrials.gov Identifier: NCT02804672 ª 2019 Mayo Foundation for Medical Education and Research
C
hronic pain is a growing public health concern, particularly among older adults. Approximately 20% of the population has chronic pain,1 defined as pain on most days or every day for the past 6 months.2 The prevalence of chronic pain increases with age; thus, it affects up to 60% of people older than 65 years.3-6 Moreover, chronic pain has a major influence on the health of older people because it leads to reduced physical activity7 and increases the risk of the frailty syndrome,8,9 falls,10,11 physical disability,12 and cognitive impairment.13 As a result, chronic pain is the leading cause of years lived with disability in people age 50 years and older.14,15
n
Mayo Clin Proc. 2019;94(9):1707-1717
The health burden of chronic pain is greater in older women than men14,15 because in most population-based studies, the frequency and intensity of pain is also higher in women.1,4-6 Compared with men, women usually have a lower pain threshold and lower pain tolerance, and they experience greater unpleasantness (or intensity) with pain.16 However, in many cases of chronic pain, no specific cause is identified (most people have “primary” pain),17,18 so the reasons for the excess pain in women versus men are not well known. A better understanding of these reasons may serve to lower the incidence of pain in older women and, subsequently, to reduce the gender
Mayo Clin Proc. n September 2019;94(9):1707-1717 n https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org n ª 2019 Mayo Foundation for Medical Education and Research
For Limelight, see page 1655 From the Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/ IdiPaz, Spain (E.G-E., I.R-S., R.O., E.L-G., F.F.C., J.R.B., F.R-A.); Centro de Investigación Biomédica en Red of Epidemiology and Public Health, Madrid, Spain (E.G-E., R.O., E.L-G., F.F.C., J.R.B., F.R-A.); Department Affiliations continued at the end of this article.
1707
MAYO CLINIC PROCEEDINGS
2008-2009 n=3289 95 deaths 675 losses to follow-up 2012 n=2519 95 deaths 600 losses to follow-up 2015 n=1824 Exclusion criteria: 103 with no information on pain in 2012 or 2015 759 with pain at baseline 94 with no information on diet and alcohol consumption 17 with no information in other potential confounders
FIGURE. Flow of participants in the Seniors-Estudio de Nutrición y Riesgo Cardiovascular en España cohort.
difference in pain and its health burden. Therefore, we conducted a mediation analysis of a cohort of older women and men in Spain to identify health behaviors and psychosocial and clinical factors that are associated with the excess risk of pain among female compared with male participants. PATIENTS AND METHODS Study Design and Participants We analyzed data from the Seniors-Estudio de Nutrición y Riesgo Cardiovascular en España cohort, whose methods has been reported elsewhere.19,20 This population-based cohort included community-dwelling individuals age 60 years and older and selected during 2008-2018 in Spain. Data were collected in 3 stages. First, a telephone interview was used to obtain sociodemographic variables, health behaviors, morbidity, and health services use. Next, 2 home visits were conducted to collect questionnaire-based information, perform a physical examination, obtain a diet history, and collect biological samples. Data were gathered by trained and certified staff members from January 1, 2012, through December 31, 2015. Information was updated 1708
Mayo Clin Proc.
n
in 2012 (wave 1) and 2015 (wave 2). Given that information on pain was first obtained in 2012, analyses for this study were conducted with the 1824 participants in 2012 who were followed up to 2015. From these individuals, we excluded those with chronic pain at baseline or incomplete data on pain and risk factors for pain in 2012 or 2015; thus, analyses were performed with 851 people (Figure). Study participants gave informed written consent. The study was approved by the Ethics Research Committee of La Paz University Hospital in Madrid. Study Variables Pain. Pain was reported using 10 items from the questionnaire used in the Survey on Chronic Pain in Europe.4 Participants reporting pain at least 2 times per week in the last 6 months were classified as suffering persistent pain; those reporting pain 1 time per week, 1-3 times per month or less than 1 time per month were deemed to have sporadic pain; and those without pain in the past 6 months were classified as having no pain. Because analyses were performed among individuals free of pain at baseline, pain variables described later provide information on pain characteristics at follow-up. Impact of pain on habitual activities of daily living was used to assess pain intensity. Participants with pain troubling them moderately, a lot, or completely were deemed to have moderate- to high-intensity pain; those with little trouble had light intensity pain; and those with no trouble had very-low-intensity pain. Participants classified as having high-, light-, and very-lowintensity incident pain reported an average intensity of 8.1, 5.0, and 2.4 points (in a scale from 1 [no pain] through 10 [a pain I cannot even imagine bearing]), respectively. Individuals reported pain in 6 localizations: (1) head and neck, (2) back, (3) bones and joints, (4) legs, (5) arms, and (6) other sites. This scale was used to classify them according to the number of pain sites: 0, 1-2, and 3. We built a pain scale based on frequency of pain, its intensity, and the number of sites. Given that we assigned a score of 1 and 2,
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
respectively, to sporadic and persistent pain, to light and moderate-high intensity, and to 1-2 and 3 or more sites, the scale ranged from 0 to 6 (worst pain). This scale serves to classify participants into 3 groups: lowest pain (0 points), middle pain (1-4 points), and highest pain (5-6 points). The cutoff point between middle and highest pain was the median score in those with a pain score of 1-6.21 Potential Mediators of the Association Between Sex and Incident Pain. Potential mediators have been selected because they were associated with pain risk in the literature16,22,23 and may have an unequal distribution in women and men. These variables were measured in 2012 and include the following. Sociodemographic Factors. Sociodemographic factors were age and level of education (primary, secondary, university). Health Behaviors. Health behaviors included tobacco and alcohol consumption, diet quality, sedentary behavior, physical activity, and body mass index (BMI). Self-reported tobacco smoking was classified as never-, former-, and current-smoking. Consumption of beverages and food was ascertained with a validated computerized diet history.24 This tool collected information on 34 alcoholic beverages, and alcohol intake was estimated using standard composition tables. Diet quality was represented by adherence to the Mediterranean diet, as summarized with the Mediterranean Diet Adherence Screener (MEDAS) score, which consists of 14 items with targets for food consumption and habits characteristic of this diet in Spain. MEDAS score ranges from 0 to 14, and a higher score indicates better adherence to the Mediterranean diet.25 For the present analyses, we excluded the alcohol component of the index (included above considered as a separate behavior), so that the modified score ranged from 0 to 13. Sedentary behavior was approximated by time spent watching television, obtained with the Nurses’ Health Study Questionnaire.26 Recreational and Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
household physical activity was derived from the European Prospective Investigation into Cancer and Nutrition cohort questionnaire and expressed in metabolic equivalents taskehours per week.27 Lastly, weight and height were measured with standardized procedures,19 and BMI was calculated as kilograms per square meter. BMI was categorized as normal weight (19.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obesity (30 kg/m2). Psychosocial Factors. Psychosocial factors included social network, housing conditions, sleep quality, and psychological distress. Social network was assessed with a questionnaire regarding marital status (yes, no), cohabitation (yes, no), daily contact with family (yes, no) and friends (yes, no), being alone at home less than 2 h/d (yes, no), and being usually accompanied while walking away from home (yes, no). We built a social network scale by assigning 1 point to each affirmative response, resulting in a range of 0-6 (greatest network).28 Individuals reported their housing conditions, which we summarized as feeling (or not feeling) cold at home.29 Participants were asked to report their quality of sleep as “very poor”, “poor”, “fair” (categorized as poor sleep), “good”, or “very good” (categorized as good sleep).30 Psychological distress was assessed with the 12-item General Health Questionnaire; it ranges from 0 to 12, with higher scores indicating greater short-term distress.31 Morbidity. Individuals reported the following physician-diagnosed diseases: cardiovascular disease (ischemic heart disease, stroke, or heart failure), chronic obstructive lung disease, diabetes, osteomuscular disease (osteoarthritis, arthritis or hip fracture), and depression requiring treatment.19 Functional Limitations. We assessed limitations in agility and mobility with the Rosow scale32 and in instrumental activities of daily living (IADL) with the Lawton-Brody index.33 Impaired agility was defined as answering “a lot” to the following question: “On an average day with your current
https://doi.org/10.1016/j.mayocp.2019.03.034
1709
MAYO CLINIC PROCEEDINGS
health, would you be limited in bending and kneeling?” The categories of response were “yes, a lot,” “yes, a little,” and “not at all.” Likewise, impaired mobility was defined as answering “a lot” to any of the three corresponding questions on (1) picking up or carrying a shopping bag, (2) climbing one flight of stairs, and (3) walking several city blocks (a few hundred meters). The LawtonBrody index evaluates independent complex living skills, including the individual’s ability to go shopping, use the telephone, prepare meals, do housework, do laundry, use different means of transportation, take medication, and manage finances. Because of cultural issues, questions about preparation of meals, housework, and laundry were not asked in men; therefore, the scale ranged 0-8 points in women and 0-5 in men. In the present analyses, a higher score indicates worse function. Finally, we also performed the Mini-Mental State Examination,34 which assesses cognitive function. The Mini-Mental State Examination scale ranges from 0 to 30 (highest functioning). Statistical Analyses Analyses were performed in 4 subsequent stages. First, we estimated the risk of middle and highest pain during follow-up in women and men; gender differences in pain risk were summarized with age-adjusted relative risk ratios (RRRs) obtained from multinomial (pain in 3 categories) logistic regression, using men as reference category (model 1). Second, we also used multinomial logistic regression to assess the association between the potential mediators at baseline and the risk of pain during followup in the total study sample. Moreover, we checked that the associations were consistent in men and women. Results are presented as age- and sex-adjusted RRR and their 95% CI. Third, we assessed gender differences in the baseline prevalence of the potential mediators of the study association. Fourth, we estimated the contribution of each potential mediator to gender differences in pain risk. To this end, we built a logistic model (model 2) in which we added each potential mediator (each at a time) to model 1710
Mayo Clin Proc.
n
1. Next, we compared the gender-associated RRR of pain risk in model 1 versus model 2. The percentage reduction in the RRR in model 2 versus 1 ([RRR2 e RRR1] 100) / (RRR1-1) corresponds to the magnitude of the mediation by each factor.35,36 Of note is that only those variables that had somewhat unequal frequency in women and men, and that showed an association with pain risk, can mediate the difference in pain risk between women and men. Statistical significance was set at 2-sided P<.05. Statistical analyses were performed with STATA (version 14.0; Stata Corp., College Station, TX).
RESULTS During a mean follow-up of 2.8 years, the incidence of middle and highest pain in women was 12.5% and 22.6%, respectively. Corresponding figures for men were 12.4% and 12.6%. Accordingly, the age-adjusted RRR of middle and highest pain in women versus men was 1.20 (95% CI, 0.79-1.83) and 2.03 (95% CI, 1.40.-2.94), respectively. Excess risk of highest pain in women resulted from an excess risk of persistent pain (RRR, 1.78; 95% CI, 1.26-2.53), moderate- to high-intensity pain (RRR, 1.92; 95% CI, 1.33-2.77), and pain at 3 or more sites (RRR, 2.45; 95% CI, 1.59-3.78) in women. The excess risk of pain in women was observed as statistically significant only for the highest pain category. Table 1 shows the association between the potential mediators at baseline and the risk of highest versus lowest pain during follow-up. Being older, overweight, or obese; having a stronger social network, poor sleep quality, or psychological distress; suffering from cardiovascular disease, chronic lung disease, or osteomuscular disease; and having limitations in agility, mobility, and IADL were all associated with increased risk of highest pain. In contrast, more physical household activity was associated with reduced risk. In addition, individuals suffering from depression or diabetes showed a nonstatistically significant increased risk of highest pain, whereas those who engaged in more
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
TABLE 1. Relative risk ratios (95% CI) for incident highest pain in 2015, according to sociodemographic factors, health behaviors, psychosocial factors, and clinical characteristics in 2012 among older adults (n ¼ 851) Highest vs. lowest pain, RRRa (95% CI)
Characteristics Sociodemographic factors
1.04 (1.00-1.07)b
Age (years) Educational level Secondary vs Primary
0.85 (0.54-1.35)
University vs Primary
1.16 (0.73-1.84)
Health behaviors Tobacco smoking Former smoker vs never smoker
1.20 (0.76-1.91)
Current smoker vs never smoker
1.02 (0.50-2.07)
Alcohol intake, gm/d
1.00 (0.98-1.01)
Mediterranean diet (MEDAS)
1.07 (0.95-1.20)
Watching TV, h/wk
1.01 (0.99-1.03)
Recreational physical activity (MET-h/wk)
0.99 (0.97-1.00)
Second vs first tertile
0.93 (0.60-1.46)
Third vs first tertile
0.76 (0.48-1.19)
Household physical activity (MET-h/wk) Second vs first tertile
0.83 (0.54-1.27)
Third vs first tertile
0.47 (0.29-0.75)b
Body mass index, kg/m2 25-29.9 vs <25
1.74 (1.06-2.86)b
30 vs <25
2.22 (1.31-3.75)b
Psychosocial factors Social network score
1.24 (1.03-1.48)b
Feeling cold at home
1.53 (0.72-3.27)
Poor sleep quality
2.24 (1.49-3.37)b
GHQ-12 sore
1.18 (1.09-1.27)b
Morbidity Cardiovascular diseasec
2.10 (1.16-3.82)b
Diabetes
1.27 (0.82-1.98) 2.09 (1.18-3.66)b
d
Chronic lung disease
Osteomuscular disease
2.64 (1.77-3.94)b
Depression
1.48 (0.84-2.59)
e
Functional limitations 3.05 (2.04-4.56)b
Agility impairment
3.14 (2.09-4.70)b
Mobility impairment Limitation in IADL
2.07 (1.22-3.53)b
Mini-Mental State Examination
1.05 (0.94-1.18)
f
GHQ-12 ¼ 12-item General Health Questionnaire; IADL ¼ instrumental activities of daily living; MEDAS ¼ Mediterranean Diet Adherence Screener (excluding alcohol); MET ¼ metabolic equivalents task; RRR ¼ relative risk ratio. b P<.05. Statistically significant results in boldface. c Ischemic heart disease, stroke, and heart failure. d Asthma or chronic bronchitis. e Osteoarthritis, arthritis, and hip fracture. f In the present analyses, a higher score in the Lawton and Brody Score indicates worse function. a
Relative risk ratios (RRR) were adjusted for age and sex in 2012 (when age was the studied mediator, adjustment was only made for sex).
Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
https://doi.org/10.1016/j.mayocp.2019.03.034
1711
MAYO CLINIC PROCEEDINGS
TABLE 2. Sociodemographic factors, health behaviors, psychosocial factors, and clinical characteristics of study participants with no pain in 2012, by sex (N ¼ 785) Men (n ¼ 484)
Women (n ¼ 367)
P value
71.3 (5.9)
72.1 (5.8)
.06
Primary
37.4
55.9
Secondary
31.2
25.3
University
31.4
18.8
Never smoker
26.6
78.2
Former smoker
59.1
17.2
Current smoker
14.3
4.6
<.01
15.7 (16.5)
3.9 (7.7)
<.01
Characteristics Sociodemographic factors Mean age, years (SD) Education level, %
<.01
Health behaviors Tobacco smoking, %
Mean alcohol intake, gm/d (SD) Mean MEDASa score (SD)
6.4 (1.5)
6.2 (1.6)
<.01
Mean time watching television, h/wk (SD)
16.9 (9.4)
19.5 (9.7)
<.01
Mean recreational activity, MET-h/wk (SD)
26.7 (16.8)
19.9 (11.7)
11.8 (6.0)
8.3 (4.8)
Second tertile
25.2 (3.8)
19.0 (2.3)
Third tertile
45.7 (13.2)
33.3 (7.5)
2.5 (2.4)
21.9 (10.6)
First tertile
<.01
Mean household activity, MET-h/wk (SD) First tertile Second tertile
14.5 (4.6)
44.7 (7.2)
Third tertile
39.2 (14.2)
80.1 (18.2)
20.7
33.2
25-29.9 kg/m
50.2
42.0
30 kg/m2
29.1
24.8
<.01
3.6 (0.9)
3.6 (1.2)
.19
4.6
5.5
.55
<.01
Body mass index, % <25 kg/m2 2
Psychosocial factors Mean social network score (SD) Feeling cold at home, %
18.2
26.4
<.01
0.7 (1.6)
1.5 (2.5)
<.01
Cardiovascular disease,b %
8.1
7.4
.71 <.01
Poor sleep quality, % Mean GHQ-12 score (SD) Morbidity Diabetes, %
25.6
15.3
Chronic lung disease,c %
7.0
10.9
.04
Osteomuscular disease,d %
38.0
58.6
<.01
Depression, %
4.8
16.1
<.01
Functional limitations Agility impairment, %
35.3
54.5
<.01
Mobility impairment, %
16.1
39.8
<.01 Continued on next page
1712
Mayo Clin Proc.
n
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
TABLE 2. Continued Men (n ¼ 484)
Characteristics
Women (n ¼ 367)
P value
Functional limitations, continued Limitation in IADL,e %
0.03 (0.2)
0.06 (0.4)
.12
Mini-Mental State Examination, mean (SD)
28.8 (1.4)
28.1 (2.0)
<.01
GHQ-12 ¼ 12-item General Health Questionnaire; IADL ¼ instrumental activities of daily living; MEDAS ¼ Mediterranean Diet Adherence Screener (excluding alcohol); MET ¼metabolic equivalents task. b Ischemic heart disease, stroke and heart failure. c Asthma or chronic bronchitis. d Osteoarthritis, arthritis, and hip fracture. e In the present analyses, a higher score in the Lawton and Brody Score indicates worse function. a
Differences were tested with an analysis of variance (ANOVA) or the chi-square test for continuous and categorical variables, respectively.
recreational physical activity had a nonsignificant reduced risk. Among the factors associated with increased risk of highest pain, chronic lung disease, osteomuscular disease, depression, poor sleep quality, and limitations in agility and mobility were more frequent in women than in men (Table 2). Compared with men, women also performed less recreational activity and had a worse score on the 12-item General Health Questionnaire. Therefore, these factors can mediate the excess risk of highest pain in women compared with men, because they are risk factors of pain (independently of sex; Table 1) and have a higher prevalence in women (Table 2). Table 3 shows the magnitude of their mediation. Specifically, osteomuscular disease, impaired mobility, and impaired agility were the largest mediating factors for the excess risk of pain in women versus men, because they accounted, respectively, for 31.1%, 46.6%, and 32.0% of the excess risk. Other relevant mediators were psychological distress (25.2%), depression (8.7%), poor sleep quality (10.7%), and lower recreational physical activity (12.6%). Of note is that some risk factors for highest pain, including excess weight, cardiovascular disease, and diabetes, were less frequent in women than in men (Table 2). Therefore, the magnitude of the excess risk of pain in women compared with men would have been even larger (15.5%, 3.90%, and 5.9%, respectively) had the prevalence of each of these factors been the same in each Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
gender (Table 3). Lastly, household activity, a protective factor for highest pain, was greater in women (Table 2). Accordingly, the excess risk of pain in women would have been 70.9% higher if women had done the same household activity as men (Table 3). DISCUSSION In this study among community-living older people in Spain, women showed a greater risk of highest pain than men did. This excess risk was partly explained by more frequent osteomuscular disease and worse physical function status in women than in men. Other mediating factors were worse mental health, particularly greater psychological distress, and lower physical activity. Our results are consistent with previous literature indicating that pain risk is higher in older women than in men.1,4-6 However, excess risk in women was limited to the most severe forms of pain, including a higher number of localizations and impact on daily activities, possibly because, compared with men, women experience greater unpleasantness with pain, suffer more comorbid pain conditions, and are more likely to develop disability from the same pain condition.16 Our results on risk factors for pain are mostly in line with previous research. Previous investigations also found that low physical activity,37-39 excess weight,40,41 poor sleep quality,42 chronic diseases43 (osteomuscular disease,43-45 cardiovascular disease,43 chronic lung disease,46,47
https://doi.org/10.1016/j.mayocp.2019.03.034
1713
MAYO CLINIC PROCEEDINGS
TABLE 3. Relative risk ratios (95% CI) for incident highest pain in women versus men, with adjustment for potential mediators, and percentage change in relative risk ratios of model 1 after additional adjustment for such potential mediators RRRa (95% CI)
Characteristics
Percentage of change in RRR
Adjusted for age (model 1)
2.03 (1.40-2.94)
d
Model 1 additionally adjusted for educational level
2.05 (1.41-3.00)
e1.9
Model 1 and tobacco
2.21 (1.42-3.42)
e17.5
Model 1 and alcohol
1.95 (1.30-2.93)
7.8
Model 1 and MEDAS
2.06 (1.42-2.99)
e2.9
Model 1 and watching television
2.00 (1.37-2.90)
2.9
Model 1 and recreational physical activity
1.90 (1.30-2.77)
12.6
Model 1 and household physical activity
2.76 (1.77-4.31)
e70.9
Model 1 and BMI (normal weight, overweight, obesity)
2.19 (1.50-3.19)
e15.5
Model 1 and social network
2.07 (1.43-3.00)
e3.9
Model 1 and feeling cold at home
2.02 (1.40-2.93)
1.0
Model 1 additionally adjusted for health behaviors
Model 1 additionally adjusted for psychosocial factors
Model 1 and sleep quality
1.92 (1.32-2.79)
10.7
Model 1 and GHQ-12
1.77 (1.22-2.61)
25.2
Model 1 and cardiovascular disease
2.07 (1.42-3.00)
e3.9
Model 1 and diabetes
2.09 (1.44-3.04)
e5.9
Model 1 and chronic lung disease
1.98 (1.37-2.88)
4.9
Model 1 and osteomuscular disease
1.71 (1.17-2.50)
31.1
Model 1 and depression
1.94 (1.33-2.83)
8.7
Model 1 additionally adjusted for morbidity
Model 1 additionally adjusted for functional limitations
a
Model 1 and agility impairment
1.70 (1.16-2.48)
32.0
Model 1 and mobility impairment
1.55 (1.05-2.29)
46.6
Model 1 and limitation in IADL
2.00 (1.37-2.90)
2.9
Model 1 and Mini-mental State Examination
2.10 (1.44-3.05)
e6.8
BMI ¼ body mass index; IADL ¼ instrumental activities of daily living; GHQ-12 ¼ 12-item General Health Questionnaire; MEDAS ¼ Mediterranean Diet Adherence Screener (excluding alcohol); RRR ¼ relative risk ratio.
diabetes,48,49 anxiety and depression43,50), and limitations in physical function51 are associated with increased risk of pain. All these health behaviors, morbid conditions, and functional impairments show bidirectional associations and can be part of the same altered health complex. For example, low physical activity can lead to excess weight, and both of them increase the risk of sleep problems and chronic diseases, and vice versa. In addition, low activity and excess weight can lead to functional impairments, usually mediated by chronic diseases. Finally, anxiety and depression frequently coexist with, and compound, many of these 1714
Mayo Clin Proc.
n
conditions. In fact, multimorbidity is a strong pain risk factor,43 and pain in one location increases the risk of pain in other sites.21,22,43 The distribution of risk factors of pain in men and women in our study is similar to that in the older general population of Spain. In the 2017 National Health Survey of Spain, conducted on a representative sample of the noninstitutionalized Spanish population, older women also showed lower recreational physical activity, less frequent excess weight, more psychological distress, and higher prevalence of osteomuscular disease, depression, and limitations in mobility and IADL
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
than their age-matched male counterparts did.52 This finding suggests that our results on the mediators of excess risk of pain in older women compared with men could be applied to the older Spanish population. In most developed countries, the sex distribution of the variables is in line with that observed in our study, but the relative importance of each mediator can vary according to the between-gender difference in its prevalence in each country. We are not aware of any previous study that comprehensively assessed a good number of potential mediators of differences in pain risk between men and women. Our study extends knowledge in this field by showing that certain health behaviors (eg, low recreational activity) and conditions (eg, osteomuscular disease, psychological distress, depression, poor sleep quality, and functional impairment), which are frequently clustered, can partly explain the excess risk of highest pain in women. Moreover, our results are clinically relevant because they suggest that improving physical function and psychological health and increasing physical activity (both recreational and at household) can be a starting point to lower pain risk in older women and reduce the gender gap in pain. In fact, there is evidence that physical activity can reduce pain onset and intensity, improve sleep quality and mood, lower the risk of chronic disease, and reduce functional limitations.37-39,53 However, future research should confirm our results in other populations and test the effectiveness of female-focused population and clinical interventions to promote physical activity and to prevent age-related declines in physical and psychological health to reduce the pain burden. Our study has several strengths and limitations. Among the former is the prospective study design, which reinforces causal inference regarding the observed risk factors of pain. In addition, the fact that the identified pain risk factors and their gender distribution were consistent with literature adds credibility to our study results. Regarding the limitations, perhaps the main one was the lack of data on many biologic mediators, Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
including genetic and omic factors and hormonal status; therefore, we could not assess their contribution to pain differences between women and men nor their interaction with the studied behavioral, psychosocial, and clinical factors. In addition, the pain questionnaire has not been validated, and we did not collect information on the type of pain (eg, neuropathic, nociceptive) and its etiology. However, we used items similar to other widely used questionnaires. In a previous article,23 we showed that the distribution of pain categories across sociodemographics, lifestyle, and chronic diseases was consistent with the literature.4-6 Lastly, morbidity was self-reported, which might underestimate its prevalence, particularly for their milder forms; however, about half of the older women and men in our study visited the primary care practitioner at least once per month,20 which limits underdiagnosis and differential diagnosis between women and men.
CONCLUSION This study suggests that a greater frequency of some chronic diseases and worse functional status as well as a lower physical activity can mediate the excess risk of pain in older women versus men. Future research should assess the role of sex-related biologic factors and their interaction with the above mediators in explaining differences in pain risk between older men and women. Moreover, it should test whether interventions aiming to increase physical activity may lower the women-associated pain burden. Abbreviations and Acronyms: BMI = body mass index; IADL = Instrumental Activities of Daily Living; MEDAS = Mediterranean Diet Adherence Screener; RRR = relative risk ratio Affiliations (Continued from the first page of this article.): of Geriatric Medicine, Hospital Universitario La Paz/ IdiPaz, Madrid, Spain (I.R-S.); and Department of Geriatric Medicine, Hospital Universitario de Getafe and CIBER of Frailty and Healthy Ageing, Getafe, Spain (L.R-M.). Grant Support: This work was supported by FIS grants 16/ 609, 16/1512, and 18/0028 (Instituto de Salud Carlos III, State Secretary of R þ D þ I, and FEDER/FSE), the
https://doi.org/10.1016/j.mayocp.2019.03.034
1715
MAYO CLINIC PROCEEDINGS
ATHLOS project (EU H2020-Project ID: 635316), and the JPI HDHL (SALAMANDER project). 17.
Potential Competing Interests: The authors report no competing interests. Correspondence: Address to Esther García-Esquinas, MD, Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo 4, 28029 Madrid, Spain ([email protected]).
REFERENCES
19.
20.
21.
1. Dahlhamer J, Lucas J, Zelaya C, et al. Prevalence of chronic pain and high-impact chronic pain among adults - United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(36):1001-1006. 2. International Association for the Study of Pain. Classification of chronic pain, second edition (revised). Available at: https://www. iasp-pain.org/PublicationsNews/Content.aspx?ItemNumber¼ 1673&navItemNumber¼677. Accessed October 25, 2018. 3. Fayaz A, Croft P, Langford RM, Donaldson LJ, Jones GT. Prevalence of chronic pain in the UK: a systematic review and meta-analysis of population studies. BMJ Open. 2016;6(6): e010364. 4. Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain. 2006;10(4):287-333. 5. Miró J, Paredes S, Rull M, et al. Pain in older adults: a prevalence study in the Mediterranean region of Catalonia. Eur J Pain. 2007; 11(1):83-92. 6. Gálvez-Barrón C, Narvaiza L, Dapena MD, Macho O, Rodríguez-Molinero A. Prevalence and treatment of pain in noninstitutionalized very old population: transversal study at national level. Aging Clin Exp Res. 2016;28(2):347-353. 7. Stubbs B, Binnekade TT, Soundy A, Schofield P, Huijnen IP, Eggermont LH. Are older adults with chronic musculoskeletal pain less active than older adults without pain? A systematic review and meta-analysis. Pain Med. 2013;14(9):1316-1331. 8. Veronese N, Maggi S, Trevisan C, et al. Pain increases the risk of developing frailty in older adults with osteoarthritis. Pain Med. 2017;18(3):414-447. 9. Bindawas SM, Vennu V, Stubbs B. Longitudinal relationship between knee pain status and incident frailty: data from the Osteoarthritis Initiative. Pain Med. 2018;19(11):2146-2152. 10. Leveille SG, Jones RN, Kiely DK, et al. Chronic musculoskeletal pain and the occurrence of falls in an older population. JAMA. 2009;302(2):2214-2221. 11. Stubbs B, Schofield P, Binnekade T, Patchay S, Sepehry A, Eggermont L. Pain is associated with recurrent falls in community-dwelling older adults: evidence from a systematic review and meta-analysis. Pain Med. 2014;15(7):1115-1128. 12. Andrews JS, Cenzer IS, Yelin E, Covinsky KE. Pain as a risk factor for disability or death. J Am Geriatr Soc. 2013;61(4):583-589. 13. Moriarty O, McGuire BE, Finn DP. The effect of pain on cognitive function: a review of clinical and preclinical research. Prog Neurobiol. 2011;93(3):385-404. 14. Buchbinder R, van Tulder M, Öberg B, et al. Lancet Low Back Pain Series Working Group. Low back pain: a call for action. Lancet. 2018;391(10137):2384-2388. 15. Institute for Health Metrics and Evaluation. Global Burden of Disease Compare. Data visualization. Available at: https:// vizhub.healthdata.org/gbd-compare/ 2016. Accessed October 25, 2018. 16. Greenspan JD, Craft RM, LeResche L, et al; Consensus Working Group of the Sex, Gender, and Pain SIG of the IASP. Studying
1716
18.
Mayo Clin Proc.
n
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32. 33.
34.
35.
sex and gender differences in pain and analgesia: a consensus report. Pain. 2007;132(suppl 1):S26-S45. Treede RD, Rief W, Barke A, et al. A classification of chronic pain for ICD-11. Pain. 2015;156(6):1003-1007. Mills S, Torrance N, Smith BH. Identification and management of chronic pain in primary care: a review. Curr Psychiatry Rep. 2016;18(2):22. Rodríguez-Artalejo F, Graciani A, Guallar-Castillón P, et al. Rationale and methods of the Study on Nutrition and Cardiovascular Risk in Spain (ENRICA). Rev Esp Cardiol. 2011;64(10): 876-882. Hernández-Aceituno A, Pérez-Tasigchana RF, GuallarCastillón P, López-García E, Rodríguez-Artalejo F, Banegas JR. Combined healthy behaviors and healthcare services use in older adults. Am J Prev Med. 2017;53(6):872-881. van Hecke O, Torrance N, Smith BH. Chronic pain epidemiology - where do lifestyle factors fit in? Br J Pain. 2013;7(4): 209-217. Hartvigsen J, Hancock MJ, Kongsted A, et al. Lancet Low Back Pain Series Working Group. What low back pain is and why we need to pay attention. Lancet. 2018;391(10137):2356-2367. Rodríguez-Sánchez I, García-Esquinas E, Mesas AE, MartínMoreno JM, Rodríguez-Mañas L, Rodríguez-Artalejo F. Frequency, intensity and localization of pain as risk factors for frailty in older adults. Age Ageing. 2019;48(1):74-80. Guallar-Castillón P, Sagardui-Villamor J, Balboa-Castillo T, et al. Validity and reproducibility of a Spanish dietary history. PLoS One. 2014;9(1):e86074. Schröder H, Fitó M, Estruch R, et al. A short screener is valid for assessing Mediterranean diet adherence among older Spanish men and women. J Nutr. 2011;141(6):1140-1145. Martínez-Gonzalez MA, López-Fontana C, Varo JJ, SánchezVillegas A, Martínez JA. Validation of the Spanish version of the physical activity questionnaire used in the Nurses’ Health Study and the Health Professionals’ Follow-up Study. Public Health Nutr. 2005;8(7):920-927. Pols MA, Peeters PH, Ocke MC, Slimani N, Bueno-deMesquita HB, Collette HJ. Estimation of reproducibility and relative validity of the questions included in the EPIC Physical Activity Questionnaire. Int J Epidemiol. 1997;26(suppl 1): S181-S189. Sánchez-Martínez M, López-García E, Guallar-Castillón P, et al. Social support and ambulatory blood pressure in older people. J Hypertens. 2016;34(10):2045-2052. García-Esquinas E, Pérez-Hernández B, Guallar-Castillón P, Banegas JR, Ayuso-Mateos JL, Rodríguez-Artalejo F. Housing conditions and limitations in physical function among older adults. J Epidemiol Community Health. 2016;70(10):954-960. Campanini MZ, Guallar-Castillón P, Rodríguez-Artalejo F, Lopez-Garcia E. Mediterranean diet and changes in sleep duration and indicators of sleep quality in older adults. Sleep. 2017;40(3). Sánchez-López MP, Dresch V. The 12-Item General Health Questionnaire (GHQ-12): Reliability, external validity and factor structure in the Spanish population. Psicothema. 2008; 20(4):839-843. Rosow I, Breslau N. A Guttman health scale for the aged. J Gerontol. 1966;21(4):556-559. Lawton MP, Brody EM. Assessment of older people: selfmaintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179-186. Escribano-Aparicio M, Pérez-Dively M, García-García F, et al. Validación del MMSE de Folstein en una población española de bajo nivel educativo. Rev Esp Geriatr Gerontol. 1999;34(6): 319-326. Wamala SP, Wolk A, Orth-Gomér K. Determinants of obesity in relation to socioeconomic status among middle-aged Swedish women. Prev Med. 1997;26(5 Pt 1):734-744.
September 2019;94(9):1707-1717
n
https://doi.org/10.1016/j.mayocp.2019.03.034 www.mayoclinicproceedings.org
GENDER DIFFERENCES IN PAIN RISK IN OLD AGE
36. MacKinnon DP, Krull JL, Lockwood CM. Equivalence of the mediation, confounding and suppression effect. Prev Sci. 2000; 1(4):173-181. 37. Landmark T, Romundstad P, Borchgrevink PC, Kaasa S, Dale O. Associations between recreational exercise and chronic pain in the general population: evidence from the HUNT 3 study. Pain. 2011;152(10):2241-2247. 38. Paley CA, Johnson MI. Physical activity to reduce systemic inflammation associated with chronic pain and obesity: a narrative review. Clin J Pain. 2016;32(4):365-370. 39. Shiri R, Falah-Hassani K. Does leisure time physical activity protect against low back pain? Systematic review and meta-analysis of 36 prospective cohort studies. Br J Sports Med. 2017;51(19): 1410-1418. 40. Okifuji A, Hare BD. The association between chronic pain and obesity. J Pain Res. 2015;8:399-408. 41. Zhang TT, Liu Z, Liu YL, Zhao JJ, Liu DW, Tian QB. Obesity as a risk factor for low back pain: a meta-analysis. Clin Spine Surg. 2018;31(1):22-27. 42. Finan PH, Goodin BR, Smith MT. The association of sleep and pain: an update and a path forward. J Pain. 2013;14(12):15391552. 43. Dominick CH, Blyth FM, Nicholas MK. Unpacking the burden: understanding the relationships between chronic pain and comorbidity in the general population. Pain. 2012; 153(2):293-304. 44. van Dijk GM, Dekker J, Veenhof C, van den Ende CH; Carpa Study Group. Course of functional status and pain in osteoarthritis of the hip or knee: a systematic review of the literature. Arthritis Rheum. 2006;55(5):779-785.
Mayo Clin Proc. n September 2019;94(9):1707-1717 www.mayoclinicproceedings.org
n
45. Bastick AN, Verkleij SP, Damen J, et al. Defining hip pain trajectories in early symptomatic hip osteoarthritis–5 year results from a nationwide prospective cohort study (CHECK). Osteoarthritis Cartilage. 2016;24(5):768-775. 46. Lee AL, Harrison SL, Goldstein RS, Brooks D. Pain and its clinical associations in individuals with COPD: a systematic review. Chest. 2015;147(5):1246-1258. 47. Christensen VL, Holm AM, Kongerud J, et al. Occurrence, characteristics, and predictors of pain in patients with chronic obstructive pulmonary disease. Pain Manag Nurs. 2016;17(2):107-118. 48. Ferreira PH1, Beckenkamp P, Maher CG, Hopper JL, Ferreira ML. Nature or nurture in low back pain? Results of a systematic review of studies based on twin samples. Eur J Pain. 2013;17(7):957-971. 49. Pai LW, Hung CT, Li SF, Chen LL, Chung Y, Liu HL. Musculoskeletal pain in people with and without type 2 diabetes in Taiwan: a population-based, retrospective cohort study. BMC Musculoskelet Disord. 2015;16:364. 50. Woo AK. Depression and anxiety in pain. Rev Pain. 2010;4(1): 8-12. 51. Thapa S, Shmerling RH, Bean JF, Cai Y, Leveille SG. Chronic multisite pain: evaluation of a new geriatric syndrome [published online ahead of print October 25 2018]. Aging Clin Exp Res, https://doi.org/10.1007/s40520-018-1061-3. 52. Ministerio de Sanidad, Consumo y Bienestar Social. Encuesta Nacional de Salud de España 2017. Available at: https://www. mscbs.gob.es/en/estadEstudios/estadisticas/encuestaNacional/ encuesta2017.htm. Accessed November 2, 2018. 53. The 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Available at: https://health.gov/paguidelines/ second-edition/report.aspx. Accessed November 2, 2018.
https://doi.org/10.1016/j.mayocp.2019.03.034
1717