Heterogeneity in the assessment of chronic pain has hindered accurate evaluation of its global burden. Yet, evidence-based treatment of chronic pain—which is both a global health priority and a fundamental human right1,2—requires accurate assessment of its prevalence and associations across cultures. Chronic pain has traditionally been viewed as secondary to failure in treatment of medical conditions like human immunodeficiency virus, cancer, or injury. However, a recent systematic literature review and meta-analysis by Jackson et al3 reported 34% prevalence of chronic pain without clear etiology in low- and middle-income countries (LMICs). This is significant, as much of the prevalent, disabling, and financially costly chronic pain in high-income countries (HICs) also lacks clear etiology, yet is clearly known to be associated with pain in multiple somatic sites, catastrophizing anxiety, psychological trauma/violence, female gender, low education and low socioeconomic status rather than any specific medical diagnosis, radiographic finding, physical abnormality, or work-related ergonomic factor.4–7 In fact, these costly chronic pain syndromes, like fibromyalgia, often begin with a discrete physical or psychological insult, but progress over time to result in widespread sensitization of all the pain and mood pathways in the central nervous system, leading to their categorization as “central sensitization syndromes” (CSS).7 Importantly, even in HICs, these CSS are typically poorly defined, underdiagnosed (prevalence 2%–12%), and ineffectively treated by strategies that discount or fail to recognize the diffuse nature of the pain or the associated psychosocial factors.7–9 This results in high direct medical costs, as well as lost productivity.10,11 Since LMIC populations, by definition, have fewer resources to devote to medical treatment and are reported to have higher overall rates of trauma, violence, and poverty, assessment tools in the future must specifically evaluate for psychosocial risk factors and pain in multiple somatic sites.7 Otherwise, we may inappropriately characterize the true nature of chronic pain and fail to effectively reduce its burden.
There is currently significant heterogeneity in the definitions of pain chronicity, periodicity, location(s), and the use (and choice) of metrics for assessment of disability, associated psychosocial risk factors, central sensitization, and pain behaviors in reported chronic pain surveys worldwide.3 The primary goal of this study was to develop and pilot a survey that concisely captures and characterizes pain chronicity, periodicity, and location and also identifies the aforementioned associated factors in 2 diverse, but representative, sociodemographic LMIC populations. Due to limited data detailing chronic pain prevalence or associated factors in Southern Asia, Nepal and India were selected for this pilot study using the Vanderbilt Global Pain Survey (VGPS), based on their close proximity, cultural heterogeneity, and World Bank income status.
The VGPS was developed to be a more comprehensive, yet concise, assessment tool for evaluating all aspects of chronic pain and its risk factors and associations. A copy of the complete survey is provided in Supplemental Digital Content 1, Appendix 1, http://links.lww.com/AA/B946. It was initially translated into both Hindi and Nepali for the purposes of our survey.
The VGPS begins with collection of standard demographic information and medical history. The next section queries chronic pain definitions, including pain chronicity, periodicity, and severity in multiple ways. These include the numeric rating scale (NRS) from 1 to 10; a series of questions to distinguish between point prevalence of any pain (“do you have pain now?”) and point prevalence of self-defined chronic pain (“do you have pain every day now?”); past incidence of chronic pain (“have you ever had chronic pain every day for 6 months?); the frequency of the pain (“is it always there or does it come and go?”); and the duration of chronic pain (0–6, 6–12 months, etc). We also asked patients to define if they believed the pain was due to a medical problem like cancer or human immunodeficiency virus, to distinguish it from pain without a clear etiology.
Several validated survey instruments were then embedded into the VGPS to capture pain-associated disability and mood disturbance. The Brief Pain Inventory (BPI), which has been validated in multiple cultures and languages (including Hindi12), was used in its entirety, with the exception of the free-form body map, where patients draw the distribution of their pain on a body schematic. The possibility of diffuse pain was instead captured using 19 categorical sites on a computerized body map, as validated by Brummett et al13 using the “Michigan Body Map.” Disability, including social and emotional disability, was assessed using the World Health Organization Disability Assessment Scale (WHODAS 2), which has been validated in the literature in multiple languages and medical conditions.14,15 Rather than using multiple time-consuming metrics to assess all possible mental health disorders, general mental health was assessed via the WHODAS 2, with questions about general “mental health” in the section of the survey related to demographics and medical history. As the chronic pain literature shows catastrophizing anxiety as a particularly strong and consistent risk factor for chronic pain,16,17 the 4-item short-form pain catastrophizing scale (PCS-4) was specifically incorporated. Preexisting psychological trauma and possible posttraumatic stress, also strong risk factors, were assessed by asking “Have you ever experienced anything you consider to be traumatic in your life?” and “Do you have nightmares or flashbacks related to this?”7
To determine the possibility of prevalent CSS, the standardized fibromyalgia survey questionnaire (FSQ) was embedded. The FSQ is a combination of the widespread pain index (WPI) and symptom severity score (SSS) and is a tool validated in the United States to assess the known risk factors for central sensitization and persistent pain in HICs.18,19
Finally, pain behavior and attitudes were also surveyed, so that future treatment and education would be more likely to be directed in a culturally acceptable manner. These questions included attitudes about how much certain treatments would be valued, in terms of distance traveled to receive them or money paid to acquire them.
Although most of these metrics have not been validated in Hindi or Nepali, they have all been previously validated in English. To preserve their validity, the metrics were incorporated without alteration into the VGPS. The surveyors also initiated a small pilot survey in the United States on 10 test participants before its implementation in India and Nepal in an effort to identify any areas of gross misinterpretation within the VGPS. No major areas of concern were identified from participants. In addition, local lead investigators in Nepal and India also reviewed each question in the VGPS to identify any socially or culturally offensive wording and provide recommendations for culturally appropriate implementation.
Participant responses were statistically analyzed to inform the following end points: prevalence of acute and chronic pain, quantification of pain intensity and timing, qualitative assessment of anatomic sites affected by those with pain, qualitative assessment of likelihood that pain is associated with another medical condition (ie, in what proportion is “pain” the only disease), qualitative assessment of treatment availability and utilization, and qualitative assessment of willingness to seek treatment for pain. Before completion of surveys, institutional review board approval was obtained both from researchers’ home institutions (Vanderbilt and University of Washington) and from the Nepal Health Research Council and the Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), one of the leading medical institutions of India, composed of a central hospital and associated primary health centers in the Union Territory of Puducherry, India. The surveys were completed in both countries between June 2014 and September 2014.
Geographic sampling areas within Kathmandu were determined based on randomization in a representative socioeconomic and cultural cohort by Nepali researchers. Households and participants were then selected using convenience sampling within each randomized area in a door-to-door fashion. Surveys were completed between 8 am and 7 pm. Variation in survey time was used in an attempt to prevent preferentially sampling only those at home or work during a given time. In India, local physicians did not feel that a door-to-door survey sample was culturally appropriate, so subjects were recruited from visitors or those accompanying patients for treatment at the JIPMER facilities. Since care at JIPMER is a free service provided under India’s recently instituted universal health care system, and sampling occurred at both the large urban hospital and its associated rural clinics in the Union Territory of Puducherry, this convenience sample was felt most similar to a community-based household sampling strategy.
The surveys were completed in both countries in accordance with the study protocol by physicians and medical students. Training for survey administration was completed before implementation to ensure consistent understanding between interviewers. In Nepal, the survey was translated into Nepali by a local investigator who spoke the native language, reviewed by local physicians, and administered to participants with surveyors recording their results. Surveyors were fluent in both Nepali and English. In India, each individual surveyor translated the VGPS into Hindi for the participants and recorded their results. The surveyors were fluent in both the local dialect and English. In each country, the surveyors administered the VGPS in the native language, and surveyors documented the responses to limit confounders including participant literacy, survey completion, and participant understanding. Participation was strictly voluntary and consisted of oral consent followed by a survey performed in a single session. Refusal rate was 0% in each country.
In both countries, inclusion criteria were any person >18 years old who was able and willing to participate. The first individual to volunteer and give oral consent based on these criteria alone was selected and only 1 person was interviewed per household or visiting family to avoid clustered familial bias in responses. Responses were first recorded on paper, and then entered into the online secured database REDCap (Research Electronic Data Capture) for management of data and statistical analysis.20 REDCap is a secure, web-based application designed to support data capture for research studies, providing (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources.20 No identifying information was collected from participants to ensure privacy, and there was no follow-up with participants after the initial survey.
In Nepal, 97 surveys were completed, while 92 were completed in India. It was not recognized until the time of data analysis that 11 people interviewed were ≤18 years old (3 in Nepal and 8 in India). These records were subsequently excluded. In both countries, the surveys took less than 1 hour each to complete.
Analyses were implemented using R (version 3.3.0) and Stata (version 12.0). Participant responses were summarized using percentages, means, standard deviations (SDs) and 95% confidence intervals (CIs). Prevalence was determined as number of positive responses divided by number of people queried. The Wilson score method was used to compute a 95% CIs for the crude prevalence of pain outcomes (ie, Figure). Parenthetical summaries of the relative prevalence were computed using the risk ratio (RR) with Wald-type 95% CI. The scores on the embedded BPI, WHODAS 2, PCS-4, and FSQ were computed per standard scoring criteria for each. To compare respondents by survey location, Fisher exact tests were used for categorical variables; Wilcoxon rank-sum tests were used for continuous variables. Although the Fisher exact test is conservative (ie, the effective type-I error rate may be somewhat smaller than the nominal type-I error rate of 5%), it was used as a substitute for the Pearson χ2 test because the latter is inaccurate when there are small cell counts. Precision analysis indicated that a sample size of 100 at each study site would be adequate to estimate a 10% prevalence of chronic pain with a 6% margin of error with 95% confidence.
Demographics and Medical History
Participant age, gender, and household size were similar in both countries (Table 1). Participant occupation, mode of transportation to the clinic/household, and method of payment for medical services differed significantly by location (all P < .001). In Nepal, most respondents listed their occupation as “service,” while in India, most worked in the home or were industrial laborers. In Nepal, the majority of patients transferred to the clinic/household through their own vehicles, while in India, the majority of the patients walked. In Nepal, 100% of patients paid for medical services in cash, while 100% of Indian respondents’ care was paid by the government. This is consistent with current literature stating that the primary means of financing health care in Nepal is via cash payment while medical care at JIPMER and associated health centers is financed by the Indian government. No one in either country reported a history of cancer, but there were statistically significant differences in the self-reported prevalence of human immunodeficiency virus/infection, osteoarthritis, and diabetes (Supplemental Digital Content 2, Table 1, http://links.lww.com/AA/B947). There were no statistically significant differences in the self-reported prevalence of cancer, heart disease, congenital deformity, intestinal problems, gynecologic problems, rheumatologic issues, neurologic disease, or mental health issues.
Chronic Pain Definitions
Pain chronicity and periodicity were assessed by multiple survey items within the VGPS due to the combination of multiple pain metrics without content alteration to preserve previously established validity. Pain chronicity and periodicity were initially queried at the beginning of the VGPS by asking “Do you have pain every day now?” and “How long have you had this chronic, daily pain?” Later within the BPI embedded in the VGPS, which was unaltered to preserve validity, patients were queried with the questions “Have you had pain other than these everyday types of pain today?” The Indian respondents reported a range of pain point prevalence from 24% to 41%, depending on the phrasing of the question within the survey, while the Nepalis more consistently reported 48% to 50% prevalence of pain on the day of the survey (Figure).
Chronic pain prevalence lasting for more than the previous 6 consecutive months was reported at 7.2% in India and 23% in Nepal (RR, 3.3; 95% CI, 1.4–7.8). When asked about ever having daily chronic pain that lasted more than 6 months, 17% of Indians and 30% of Nepalis answered in the affirmative (RR, 1.7; 95% CI, 0.99–3.0). Chronic pain was described as intermittent by 66% of Indians and 72% of Nepalis (RR, 1.1; 95% CI, 0.8–1.6).
The pain severity was surveyed in 2 ways, based on the validated metrics included in the survey, in both countries. When asking only those with pain on the day of the survey to use an NRS to describe pain severity (0 = no pain, 10 = worst pain), Indians reported a mean pain score of 5.2 (SD, 1.5; 95% CI, 4.7–5.6) while Nepalis reported a score of 2.8 (SD, 1.3; 95% CI, 2.4–3.2). When asked later during the standardized portion of the BPI embedded in the VGPS to rate the worst, best, and average pain in the past 24 hours, and pain “now,” the mean pain severity scores, excluding those who reported no pain, were 4.5 (SD, 2.3; 95% CI, 3.7–5.4) for Indians and 3.2 (SD, 1.6; 95% CI, 2.8–3.7) for Nepalis (Table 1).
Disability was assessed using the WHODAS 2 (Table 2) and BPI (Table 3), which were embedded in the VGPS. The answer to each WHODAS 2 disability scale question was graded from 0 (none) to 4 (extreme disability); since there were 12 disability questions and 4 possible positive answers, the sum or “total score” was used to estimate total disability, with 48 representing complete disability. Nepal reported a total disability score of 5.7 (SD, 8.6; 95% CI, 4.0–7.4) with approximately 8 days with some form of disability within the past month. Indian respondents had a similar total disability score of 5.2 (SD, 8.6; 95% CI, 3.4–6.9) but with close to 6 days with some form of disability within the past month. Markers of disability as assessed in the “pain interference” section of the BPI were graded on a scale of 0 (no disability) to 10 (complete disability); all mean scores in both countries were 2.1 or less.
Disability related to catastrophizing anxiety was intended to be assessed by the PCS-4. The 4 items described in the validated PCS were incorrectly entered into our REDCap database. Instead of including the 4-item short-form PCS, the first 4 questions of the full 22-item PCS were used. Therefore, rather than having a representative sample from each of the domains relevant to catastrophizing (rumination, magnification, and helplessness), our survey primarily addressed rumination. Therefore, we were not able to compare our results to any validated catastrophizing scale. Furthermore, in India, instead of grading each of the 4 statements on a scale of 0 (never) to 6 (always), as it was intended, the respondents were instructed that they could only pick 1 of the 4 statements. Of the 92 respondents to the survey in India, 28% answered 1 of the 4 questions. Of the 25 who reported some catastrophizing thought, 18 people said “I worry about it all the time and don’t think it will ever end.” In Nepal, the average score to each question was roughly 2.0 with an SD of around 1.0 on a scale from 0 to 6; however, many respondents declined to answer more than 2 of the 4 questions, feeling that it was redundant.
In another attempt to query disability secondary to psychological distress, subjects were asked if they had experienced events considered to be traumatic in their lives. Thirty-nine percent of the Nepali patients and 4% of the Indian patients reported having experienced an event they considered traumatic (39% vs 4%; RR, 9.0; 95% CI, 3.3–24.2; P < .001), with 24% of Nepalis and 50% of Indians reporting nightmares or anxiety about it, respectively (RR, 0.5; 95% CI, 0.2–1.5; P = 0.29).
Interestingly, no Indians and only 1% of Nepalis reported “mental health issues” in their list of medical conditions, despite the possible catastrophizing and trauma history in some subjects reported in other parts of the survey.
Results of the FSQ (which combines the WPI and symptom severity scores) are listed in Table 4. The SSS was calculated using the sum of 6 self-reported symptoms (fatigue, trouble thinking or remembering, waking up tired [unrefreshed], pain or cramps in lower abdomen, depression, headache), ranging from 0 to 12. The WPI was summarized using the sum of 19 pain areas, ranging from 0 to 19. The FSQ represented the sum of the 0 to 12 SSS and the 0 to 19 WPI, and its range was 0 to 31. A patient was diagnosed as FM if a WPI ≥7 and an SSS ≥ 5 or the WPI was 3–6 and the SSS ≥9. There was only 2% prevalence of fibromyalgia in both countries.
Pain Attitudes and Behaviors
Finally, both Nepal and India had varying, and sometimes surprising, attitudes and behaviors related to chronic pain (Table 5). The vast majority of participants in both countries had sought treatment for pain at some point in their lives, and everyone surveyed felt that the treatment of pain was important. Among those who sought treatment for pain, in India 100% of those reported seeking pain management from a physician versus 82% in Nepal (RR, 0.86; 95% CI, 0.79–0.93; P = .019); all but 1 participant at each site had tried pills for pain relief (P = .49), but yoga (8.6%; P = .10), herbal therapy (2.2%; P > .99), and procedures (2.2%; P > .99) were only used in Nepal. Although most respondents in both countries said they would take a pill for their pain, talk about their pain in a group, or consider movement therapy to treat their pain, 32% of Nepali respondents would pay more than $20 for pain treatment while none of those surveyed in India would be willing to pay this same amount to treat their pain.
Summary and Implications
In summary, the first implementation of the VGPS has provided useful information highlighting the difficulty in standardizing and creating concise, accurate pain assessment instruments to gather accurate data about pain chronicity, disability, and associated psychosocial risk factors among patients with diverse cultural backgrounds. The phrasing and timing of questions about pain chronicity, intensity, and disability (even within the context of previously validated tools) may lead to confusion or inaccurate interpretation. Accurate and consistent assessment of mood as it relates to pain was not possible in this iteration of the VGPS, but future modifications can capitalize on trends found thus far.
Ongoing attempts at standardized, consistent, cross-culturally relevant assessment tools like the VGPS will be critical to provide accurate baseline data from which to develop rational treatment plans for chronic pain in low-resource areas. Consensus statements and policy proposals clarifying which queries should be included in future surveys, and how they should be administered to maximize accuracy, should be prioritized. This pilot study of the VGPS—and the analysis of results within 2 culturally distinct Asian countries—is an important first step in clarifying and standardizing assessment future tools.
Prevalence and Chronic Pain Definitions
Despite limitations regarding possible survey interpretation and translation, there are several indications that the prevalence, chronicity, and severity data collected within each country using the VGPS are valid. The prevalence data for chronic pain from the VGPS, even considering small sample sizes, are consistent with previously published global data. The prevalence of chronic pain in LMICs in general populations has been estimated to be between 33.9%7,21 and 41.1%,22 but such estimates are based on heterogeneous data and inconsistent reporting tools in LMICs. Point prevalence of pain (not otherwise specified) in the VGPS was 41% in India and 50% in Nepal. When respondents were asked if they had ever had chronic pain for longer than 6 months, 17% of Indians and 30% of Nepalis said yes.
Although reasons for a relatively high pain prevalence in Nepal in our study cannot be determined at this time, the VGPS data are consistent with a survey done in the rural Sunsari District of Nepal, which reported an identical 50% prevalence of pain.15 Prevalence data in India from the VGPS are also consistent with previously published reports. Dureja et al23 polled 5004 respondents from 8 cities across the country in 2014. The overall point prevalence of chronic pain in this study was 13%. Results from the VGPS straddled this value: 17% of Indians reported having chronic pain >6 months at some point in their lives and 7% reported pain >6 months on the day of the survey. In the future, we plan to adjust the validated metrics included in the VGPS to eliminate assessing chronic pain prevalence repetitively. This would prevent confusion among survey participants while also allowing more accurate correlation between chronic pain prevalence data collected with the VGPS and current published estimates for LMICs.
The current heterogeneity in global prevalence data mirrors the difficulty we found in accurately assessing something as “straightforward” as pain chronicity in the VGPS. When asked at the beginning of the survey, “do you have pain today?” (Figure, column 1), 41% of Indians and 50% of Nepalis answered in the affirmative. Later on in the survey, during the standardized BPI question embedded in the VGPS, the patients were asked this slightly differently: “Throughout our lives, most of us have had pain from time to time (such as minor headaches, sprains, and toothaches). Have you had pain other than these kinds of everyday pain today?” When asked that way (Figure, column 2), 24% of Indians and 48% of Nepalis (versus 41% and 50% earlier) then said yes. Future surveys should note that the timing and delivery of even a simple question about point prevalence of pain (acute or chronic) may have confounding effects on the response, perhaps reflecting subjects’ desire to adjust their answers based on their perception of or comfort with the interviewer, or even confusion in the semantics, translation, or interpretation of terms like “daily,” “everyday,” and/or “every day” pain. Based on these data, removal of redundant questions addressing point prevalence and chronicity within the VGPS in future iterations intends to improve confusion for participants and limit cultural interpretation.
Queries of pain severity posed in different ways in the VGPS also led to conflicting results. This was primarily because 1 query was predicated on an affirmative answer to a previous question, and the other was a series of consecutive questions rating “worst, least, average, and current” severity over the last 24 hours. However, Indian survey by Dureja et al23 reported a mean NRS pain score of 6.93, which is consistent with one calculation of pain severity in the Indian VGPS (5.2). This further highlights the need to remove repetitive questions assessing pain severity by adjusting the validated metrics included in future versions of the VGPS.
The embedded WHODAS 2 scores revealed patients in Nepal had significant disability with some form of disability being present close to one third of the days in the month. However, there were relatively few days in which patients in Nepal were completely unable to perform usual activities or work or had to cut back or reduce usual activities or work because of any health condition. Also, within the BPI, when self-rating general psychoemotional markers of disability (like “normal work,” “enjoyment of life,” and “mood”), the Nepali cohort had low individual and mean scores for daily pain interference. The measure of pain interference in “general activity” had the highest response (1.2 [SD, 1.9; 95% CI, 0.9–1.6]) within this survey population, which is still relatively low considering the significant total number of days with some disability present which was recorded in the WHODAS 2.
Based on survey responses in India, the WHODAS 2 scores indicated that some form of disability was present close to 19% of the days in the past month. Those surveyed in India also had very few days in which disability completely prevented or reduced their ability to perform daily activities or work. Interestingly, the BPI responses again revealed extremely low levels of pain interference when querying psychoemotional markers of disability including “sleep” and “relations with others.” Pain interference in “general activity” was the highest reported disability (2.1 [SD, 2.6; 95% CI, 1.5–2.7]) based on results from the BPI portion of the survey.
Overall, the WHODAS 2 revealed a relatively high prevalence of some form of disability within the past 30 days, while the BPI indicated a much lower level of disability in both countries despite culturally diverse populations and methods of health care administration. This indicates that how disability is measured in LMICs can significantly alter our assumptions, despite the use of previously validated metrics.
Less than 16% of participants in either country reported significant problems with the WHODAS 2 items that queried the emotional or social effects of pain, like having problems participating in community activities or maintaining a friendship. Although disability as measured on the WHODAS 2 was higher in Nepal, results in both countries indicated a low level of self-reported physical or emotional disability related to pain. The presence or types of government disability programs have been associated with differences in self-reported disability rates globally,24,25 so differences in social support systems may be relevant here as well. More research is needed.
As has been detailed elsewhere in the World Mental Health Surveys, psychological distress is a significant contributor to disability, but is particularly difficult to assess across cultures in a consistent and in-depth way.26–28 Pain associated with psychological conditions was not well elucidated with the VGPS. This is not surprising given a recent review focusing on mental health disorders in Southeast Asian immigrants, which identified somatization and domestic violence as likely barriers to diagnosis.29
No one described psychological trauma or sexual violence as the inciting event for his or her pain in either country, although 1 person in Nepal reported pain that started with physical violence. Yet, 1 in 3 women is reported to experience physical or sexual violence worldwide,30 so this would seem like a gross underestimate. Given the reports of modesty and privacy as a cultural norm by local interviewers in both countries, the question arises if this information would be likely to be accurately divulged. Without using the terms “anxiety, depression, posttraumatic stress, or mental illness,” we attempted to inquire about the psychological trauma that is a risk factor for chronic pain in our survey. Although we were unable to accurately quantify catastrophizing due to technical errors, some catastrophizing thought was present in up to one fourth of those surveyed in each country, and life trauma and flashbacks were reported in many (both higher in Nepal). This indicates that improved survey standardization in the future may provide further insight into the impact of catastrophizing behavior on chronic pain in LMICs. Still, self-report of “mental health issues” was virtually nonexistent in either country. It is clear that the method of query about mood and mental health may be subject to significant cultural bias, and expert consensus between international experts and local experts will be necessary to ensure accurate assessment in a given location.
Since the metrics to determine central sensitization involve mood questions, they also may be affected by these cultural differences. Nepalis did display individual markers of central sensitization based on 24% of patients reporting pain in at least 2 somatic sites and 8% experiencing pain in 4 or more locations. In India, only 11% of those surveyed had pain in at least 2 somatic sites and only 2% indicated pain was present in 4 or more locations. Yet, the calculated prevalence of fibromyalgia was 2% in both countries, consistent with previously reported prevalence in LMIC.7 Although the intent of our survey was not to compare the 2 countries, it is interesting to note that Nepal appears to have a greater population-based risk for chronic pain overall, which supports its higher prevalence of chronic pain compared to India. In addition to a higher response rate of pain in more somatic sites, Nepalis also reported higher rates of disability and mood disruption, all of which have long been shown as risk factors for the development of chronic pain in HICs.31 Since our results were powered to estimate a 10% difference in prevalence, it is possible that CSS like fibromyalgia may well be more prevalent in Nepal and could be detected accurately by the FSQ in larger population surveys in the future.
It is important to note that our survey was done before the catastrophic earthquake in Nepal affecting the surveyed area of Kathmandu in April 2015, so that is unlikely to have contributed to the VGPS findings. The reasons for the differential prevalence and risk factors between the 2 countries will require further study and could be related to either differences in survey administration, population selection (and bias), or cultural factors.
Pain Attitudes and Behavior
Finally, cultural attitudes in both Nepal and India show that pain management is universally considered to be important, but that different health care systems and geographical access will significantly affect what choices are most desirable and relevant to the population. The most glaring difference is that 100% of Indians were covered under government insurance for health care at JIPMER and associated health centers where participants were surveyed, while 100% of the surveyed Nepalis paid cash. Hundred percent of those reporting pain in India also reported seeking pain management from a physician, although this likely reflects the fact that the subjects were all interviewed in a hospital setting and not in their homes. In the community surveys in Nepal, pain treatment was primarily, but not exclusively, sought from a physician (82%). Virtually everyone surveyed in both countries had tried pills for pain relief. However, in Nepal, yoga (8.6 %), herbal therapy (2.2%), and procedures (2.2%) were also trialed. No other modalities were reported in the Indians surveyed.
Despite a minority reporting that they had sought out any psychological or movement therapy for their pain in either country, the majority of those surveyed in both countries said they would feel comfortable talking about their pain with other people in their community and would be willing to participate in a group therapy if it would teach them how to move and/or cope with pain more effectively. Interestingly, more respondents in both India and Nepal said they would travel farther for this sort of group therapy than for a pill. Thirty percent of Nepalis (and 19% of Indians) would travel more than 10 km for a group or movement therapy as opposed to only 6% of Indians and no Nepalis who would travel >10 km for a pill. Furthermore, 95% of Nepalis would be willing to pay >$5 for a pill, while 78% of Indians would not. These cultural differences and attitudes are critical to note in any survey meant to provide a foundation for treatment initiatives.
Limitations and Conclusions
The pilot of the VGPS used a small, but very detailed interview strategy to guide the acquisition of standardized information to objectively identify attitudes, behaviors, and standardized metrics of pain and disability using 2 cultures in a timely and feasible manner. In consideration of this research design, there are inherent limitations and biases. Results cannot be used to make assumptions about areas outside of the Kathmandu District or the Union Territory of Puducherry, although the data are consistent with larger surveys within these countries. Also, the intent of our study was not to compare these 2 populations but to guide the development of a standardized metric to assess pain prevalence, chronicity, and contributing psychosocial factors in 2 different sociodemographic LMICs. However, it is interesting to note differences in responses regarding disability, mood disturbances, and somatic pain sites based on responses to this pilot survey. In future versions of the VGPS, additional auxiliary variables (eg, marital status, urban/rural), including local-specific variables (eg, ethnicity, religion) will be collected to ensure that survey weighting (and thus inferences about broader populations) is possible. Further limitations in India included surveying at only JIPMER and its associated rural clinics where 100% of the respondents’ care is provided by the government. This was based on local physician recommendation and cultural norms.
Sample size and implementation errors precluded our efforts to get accurate data on the novel aspects of catastrophizing and central sensitization that were unique to our survey; we will increase the size of our sample and correct the errors in administration of the catastrophizing scale while also providing more extensive surveyor training in the next iterations of our survey. Ideal administration remains in a community setting, as some of the differences in our Indian data may be attributable to selection bias from those accompanying family members or friends to a hospital. When implementing the VGPS in additional countries, we also plan to translate the survey into the native language and then back into English by an independent translator to ensure translational integrity and validity before data collection.
The slight discrepancies between prevalence in our data and larger national surveys in India may certainly be attributed to selection bias at JIPMER and associated rural clinics, but the tendency for pain severity (and even point prevalence of pain) to significantly change during the course of the surveys signals a need for a single, clear, and consistent approach to queries about pain definitions and chronicity in future iterations of the VGPS. Cultural bias is always a possibility, and collaboration with local researchers and formal training before any survey administration will be key.
One of the most interesting findings is that long-standing, standardized, and cross-culturally validated metrics like the BPI may not provide clinically useful information for accurate assessment or comparison of pain, mood, and disability within countries. For instance, the body map of the BPI is not able to give categorical detail about multiple somatic sites; therefore, we chose the Michigan Body Map to more accurately assess individual sites of pain. Also, the question about daily pain in the BPI uses the phrase “everyday pain like toothache,” which is misleading as it implies “everyday” pain like a chronic toothache is normal and also that “everyday” is different from chronic pain that occurs “every day.” Also, at least in our small sample, the portion of the BPI meant to assess mood and disability is not as sensitive as that of the WHODAS 2, for example. It is possible that entirely new survey tools, including future modifications of the VGPS, should be created and validated based on this information. In future iterations of the VGPS, we plan to adjust the validated metrics included in the survey based on the limitations found at identifying mood and disability during our initial pilot study.
However, despite these limitations, our results have helped to identify potentially important trends and potential semantic difficulties that may be used to inform larger surveys in multiple areas. Phrasing of questions about pain chronicity and intensity should be clear and nonrepetitive, although the ideal order for placement of these queries in the survey is unclear. Accurate and consistent assessment of mood should be culturally appropriate and targeted toward short, valid metrics that specifically address catastrophizing and psychological trauma. Larger survey sizes will be needed to sensitively detect markers of central sensitization and mood disruption; and disability metrics like the WHODAS 2 are likely to be more sensitive than older validated scales like the BPI. Based on the limitations identified with this pilot study of the VGPS, future iterations will require careful selection of validated metrics to detect disability, catastrophizing, and psychological trauma along with rigorous validation of additional questions that may better characterize the global burden of pain in LMICs. International expert consensus statements regarding standardized chronic pain definitions and the most useful metrics for querying all the relevant associations with chronic pain are critically needed to ensure adequate evaluation and treatment of this growing global burden.
Name: Jenna L. Walters, MD.
Contribution: This author was the co-primary investigator and helped revise the manuscript.
Name: Kelly Baxter, BS.
Contribution: This author helped collect data and survey administration in Nepal.
Name: Hannah Chapman, BS.
Contribution: This author helped collect data and survey administration in India.
Name: Tracy Jackson, MD.
Contribution: This author was the co-primary investigator and helped original manuscript and survey construction.
Name: Adinarayanan Sethuramachandran, MBBS, DA, DNB.
Contribution: This author helped survey administration and translate the manuscript in India.
Name: Marcus Couldridge, AD.
Contribution: This author helped collect the data.
Name: Hem Raj Joshi, MBBS, MD.
Contribution: This author helped survey administration and translate the manuscript in Nepal.
Name: Pankaj Kundra, MBBS, MD, MAMS, FIMSA.
Contribution: This author helped survey administration and translate the manuscript in India.
Name: Xulei Liu, MS.
Contribution: This author helped analyze the data.
Name: Divya Nair, MBBS, MD.
Contribution: This author helped survey administration and translate the manuscript in India.
Name: Bonnie Sullivan, BS.
Contribution: This author helped collect the data.
Name: Matthew S. Shotwell, PhD.
Contribution: This author helped analyze the data and revise the manuscript.
Name: Ryan J. Jense, MD.
Contribution: This author helped collect the data.
Name: Nicholas J. Kassebaum, MD.
Contribution: This author helped collect the data.
Name: K. A. Kelly McQueen, MD, MPH.
Contribution: This author was the senior investigator.
This manuscript was handled by: Angela Enright, MB, FRCPC.