Chronic pain affects 50 million adults in the United States (US) and is the third most common reason people seek medical treatment.1,2 Lower back pain (LBP) has a lifetime prevalence of 80% according to the National Institutes of Health’s Institute of Neurological Disorders and Stroke.2 According to the global burden of disease study, LBP is the leading cause of years lived with disability and it has held this position from 1990-2017.3 LBP affects women more than men, with non-Hispanic Whites reporting the highest prevalence among all ethnic groups.4 Although adults aged 45-64 years recorded the highest LBP rate (33.3%), adults 65 years and older reported LBP prevalence (32.8%) that still poses a public health problem.4 The average charge for LBP hospital in-patient visit was 129% more than the average charge for other in-patient visits.4 This increased hospital cost in conjunction with increased length of hospital stay for older adults with LBP could exacerbate staff shortages and may contribute to an increased financial burden on the healthcare system.

Studies have suggested that a diet aimed at reducing inflammation, and those that support the microbiome, may help alleviate chronic pain through various neurochemical pathways.5 Further, obesity, a complex association of dietary interactions and physical activity levels, may also add to the overall risk profile for development of LBP.6 Diabetes and chronic LBP may also be comorbid, especially in males.7

Epidemiological studies on back pain in general, indicate that risk increases with age, and that common comorbidities include cardiovascular disease, obesity, asthma, tranquillizer dependence, panic attacks along with other conditions.8,9 These studies indicate that diet-related disease, along with back pain, is increasing in epidemic proportions. In addition, poor nutritional status is also associated with unhealthy aging in adult wellbeing.10 The United States Department of Agriculture (USDA) recommends 1,600-2,200 kcal per day intake in women and 2,000-2,600 kcal for men who are 60 years and older.11 While aging adults have the highest diet quality compared to other age groups, older adults still fail to adhere to the recommended daily caloric intake, resulting in a score of 63 out of 100 on a healthy eating index.11 Increasing dietary consumption of fruits, vegetables, and diary, maximizing protein consumption by choosing from an assortment of protein sources, reducing intake of added sugar, sodium, and saturated fat, may all address the unmet dietary recommendation and could contribute to proper prevention and management of chronic diseases.11 Furthermore, an active lifestyle contributes to healthy aging. Older adults who engage in at least 2.5 to 5 hours of moderate-intensity aerobic activity every week are more likely to improve their balance and bone strength than their counterparts who do not.12 Likewise, active lifestyle in older adults improves quality of life and decreases symptoms of depression and anxiety.12 The objective of this paper is to explore the relationship between nutritional risk and general musculoskeletal pain and specifically, LBP.



Using the University of Alabama-Birmingham Study of Aging dataset, we examined this relationship among 1000 community-dwelling older Alabamians (>65 years) who were initially queried between 1999-2001 and assessed for basic demographics, mobility, social information, medical and health services utilization history.13 The initial assessment was conducted in-person, in the respondent’s home. Follow-up was based on interviews every 6 months, for up to 8.5 years and investigators for the initial research on the sample followed patients until death, admission to a nursing facilities or when they could no longer be reached or refused to respond.

Outcome Variable: Low Back Pain

Among the questions included in the baseline assessment is one that asks, “Tell me the parts of your body where you have had pain in the past 4 weeks… lower back.” We used responses from this question as a dichotomous variable.

Primary Predictor Variable: Nutritional Risk

We used the DETERMINE Checklist14 which asks patients about having poor appetite, skipped meals, high alcohol use, oral health problems, financial difficulties, eating alone, polypharmacy, excessive weight changes (greater or less than 10 pounds), and shopping difficulties. Scores in the original measure range from 0 (lowest risk) to 21 (highest risk); however, in this study, one item, “I eat few fruits or vegetables, or milk products,” was not ascertained, resulting in scores ranging from 0–19. Values of ≥6 indicate high nutritional risk; 3–5 indicate moderate risk, and 0–2 indicate low risk as well as assessing presence and severity of LBP over the past 4 weeks.

Control Variables

We included age as a continuous variable; sex as male vs. female; and race as black vs. white. We also included body mass index (BMI) which is defined as weight in kilograms divided by the square of height in meters.15 We included the Geriatric Depression Scale short form, a 15-item questionnaire that assesses depressive symptomology; scores range from 0 to 15 and affirmative responses on more than 5 questions indicate that depression is present. In this analysis, the variable was treated as linear.14

Cardiovascular Disease, Diabetes, Cancer

We verified diagnoses of cardiovascular disease, diabetes, cancer with 1 or more of following: 1) a self-reported physician diagnosis and prescribed medication for the condition, which was documented at the in-home visit; 2) physician-reported diagnosis on a questionnaire about the participant completed by the healthcare provider; or 3) diagnosis on hospital discharge records within 3 years of the baseline interview.

Data analysis

Data were analyzed using SPSS (IBM, 2019. Version 26. Armonk, NY). We completed univariate and bivariate analysis. We also completed ordinary least squares regression, treating nutritional risk as a continuous outcome and a second model using multivariate logistic regression in a model in which we treated nutritional risk categorically, according to the ranges prescribed in the instrument. In both multivariable models, we adjusted for factors sex, body mass index, depression, and co-morbidities.

The UAB Study of Aging was reviewed and approved by the UAB Institutional Review Board.


Seventy percent of those with LPB were either overweight or obese, compared to 68% who did not experience LBP and this was not statically significant. More than half of the participants were at nutritional risk (55.2%). An overall nutritional risk score for those with LBP was 4.3 compared to 2.9 among those without LBP (p<0.001). Table 1 contains data on demographics and risk profiles. Those with LBP were also more likely to score higher on the Geriatric Depression Scale (p <0.01) as well as to have cardiovascular disease (p<0.01).

Table 1.Relationship between participants’ characteristics and lower back pain
Lower back pain
Characteristics No (638) Yes (362) P-value
Age 75.4 ± 6.9 75.1 ± 6.5 0.47
Female 334 (52.4%) 167 (46.1%) 0.06
Male 304 (47.6%) 195 (53.9%)
Black 321 (50.3%) 179 (49.4%) 0.79
White 317 (49.7%) 183 (50.6%)
BMI 27.5 ± 6.2 28.6 ± 6.3 0.01
Depression 2.0 ± 2.1 3.0 ± 2.6 0.00
Dis 211 (33.1%) 151 (41.7%) 0.01
Diabetes 151 (23.7%) 101 (27.9%) 0.14
Cancer 118 (18.5%) 59 (16.3%) 0.38
Nutritional Risk
Overall Score 2.9 ± 2.6 4.3 ± 3.1 <.00
Normal 330 (51.7%) 118 (32.6%) <.00
Moderate 214 (33.5%) 126 (34.8%)
High 94 (14.7%) 118 (32.5%)

Note. BMI, Body Mass Index; GDS, Geriatric Depression Scale; *t-test; Chi-square test.

Result from the DETERMINE checklist are presented in Table 2. Of note, patients with low back pain were statistically more likely to report having a poor appetite due to illness or condition (p<0.001), oral health problems making it difficult to eat (p<0.001), financial difficulty buying food (p<0.001), polypharmacy (p<0.001), and not always being physically able to shop, cook, or feed themselves (p<0.001).

Table 2.Item-wise Score of Nutritional Risk Assessment by Lower Back Pain
Total Lower Back Pain
No Yes P-value
Poor Appetite 172 (17.2%) 93 (54.1%) 75 (45.9%) 0.003
Skipped Meals 31 (3.1%) 16 (51.6%) 15 (48.4%) 0.153
High Alcohol Use 34 (3.4%) 24 (70.6%) 10 (29.4%) 0.402
Oral Health Problems 134 (13.4%) 64 (47.8%) 70 (52.2%) 0.000
Financial Difficulty 132 (13.2%) 67 (50.8%) 65 (49.2%) 0.001
Eats Alone 319 (31.9%) 198 (62.1%) 121 (37.9%) 0.436
Polypharmacy 825 (82.5%) 498 (60.4%) 327 (39.6%) 0.000
Excessive Weight Change 292 (29.2%) 176 (60.3%) 116 (39.7%) 0.136
Shopping Limitations 276 (27.6%) 118 (42.8%) 158 (57.2%) 0.000

In mulivariate analyses (Table 3), 1-point increases in nutritional risk were associated with a 15% increase in the likelihood of LBP [95% CI (1.09,1.21)]; in categorical analyses, moderate nutritional risk and high nutritional risk were associated with an increase in likelihood of LBP [48.2% (95% CI 1.07,2.02) and 67.4% (95% CI 1.80,3.94)], respectively.

Table 3.Independent association between nutritional risk and lower back pain
Multivariate analysis Overall Risk Score 0–19 Categories of Risk Low, Moderate, High*
Exp(B) 95% (CI) P-Value Exp(B) 95% (CI) P-Value
Sex, female 1.17 (0.89,1.54) 0.28 1.19 (0.90,1.56) 0.23
BMI 1.03 (1.01,1.06) 0.01 1.03 (1.01,1.05) 0.01
Depression 1.1 (1.03,1.17) 0.01 1.11 (1.04,1.18) 0.00
Cardiovascular Disease 1.26 (0.95,1.68) 0.11 1.26 (0.95,1.68) 0.12
Diabetes 0.92 (0.67,1.28) 0.63 0.94 (0.68,1.31) 0.73
Nutritional Risk 1.15 (1.09,1.21) 0.00 N/A
Moderate N/A 1.47 (1.07,2.02) 0.02
High 2.66 (1.80,3.94) 0.00


To ourknowledge this is the first study to assess the relationship between nutritional risk and LBP. Our analyses revealed multiple demographic and nutritional risk factors that were associated with an increased likelihood of reporting back pain.

Our results were consistent with several other studies evaluating risk factors for lower back pain including depression, diet quality, comorbidities, etc. Depression scores were higher in those with LBP than those without, a finding in line with known psychosocial factors related to pain.14 Older adults are likely to experience incapacitating lower back pain especially those who have less social ties as a result of depression.15,16 This corresponded with the findings of Jacob and colleagues who confirmed that loneliness and depression was an independent predictor of developing persistent LBP in individuals aged 70 years.17 Low back pain was twice as likely to occur in older adults at the 4-year follow-up who recorded a high depressive symptom score at baseline.18 Our analysis also supports previous work showing an association with increased body weight and reporting of LBP.9 Those with LBP were also more likely to have cardiovascular disease than those without, supporting the result of the study, which found an association between cardiovascular risk factors - systolic blood pressure, serum triglyceride level, current smokers - and lower back pain.19 Overall DETERMINE checklist scores as a metric of nutritional risk was higher in those reporting LBP than those without (4.3 vs 2.9).

There were several specific determinants of nutritional risk that were associated with reporting of LBP. Having a poor appetite due to an illness or health condition, oral health problems making it difficult to eat, financial difficulty buying food, polypharmacy, and physical shopping limitations were all more likely to be reported by those with back pain than those without. Likewise, an analysis of a population-based data set (NHANES cycle 2009-2010) using the Healthy Eating Index 2015 found an association between low diet quality and spinal pain.20 More precisely, high quality diets including higher fruits, fiber, dairy intake and whole grain resulted in a 20% to 26% decreased likelihood of chronic spinal pain.20 Furthermore, diets high in added sugars, sodium and saturated fats were associated with spinal pain. Wong et al recorded similar results as social conditions tend to affect risk exposure such as poor eating habits leading to obesity which in turn affects the onset and persistence of low back pain.16 In contrast to our findings, however, higher BMI has been shown to be significantly associated with increased incidence of lower back pain in other studies.21 These results should not be interpreted as causal. Further, the typical limitations of secondary data analysis are implied, and findings may not be generalizable to the entire United States population.

Implications for Chiropractic Care

The multiple interrelated factors noted in this study, including depression, BMI, nutritional risk, and LBP underscore the importance of chiropractic providers remaining open to at least screening, if not treating for multiple comorbid conditions in their practice. The overwhelming majority of patients seeking chiropractic care do so because they have neck or back pain.22 Previous reports on the amount of preventive care and health education within a primary care setting suggest that it is rendered to a minority of patients.23 These findings suggest that those coming into a clinical setting need health education interactions for conditions such as overweight BMI and that screening and education around topics including depression and nutritional risk are warranted as well. Chiropractors are trusted sources of health information and should use their rapport with patients to advance their overall wellbeing, not just the condition-specific complaints with which they present at the office. Further, since health education interventions occur in an underwhelming minority of primary medical care visits, the nature of the length and multiple sessions typical of a chiropractic or complementary care provider visit could offer necessary dose response effects to messaging on health topics in this setting.24 There is a great need for healthcare workers and stakeholders to recognize and address social factors affecting the onset and persistence of low back pain. Doctors of chiropractic wishing to advise on health and wellness may want to begin with regular users of care and emphasize the positives associated with changing a health behavior, versus the negatives not making a change.25 Promoting a healthy dietary habit should be a collective public health effort. Older adults could benefit from health education by health care professionals; older adults should be encouraged to enjoy meals with friends and family, explore different foods options, as well as maintain a good oral hygiene.11 These health tips could create awareness on availability of healthy food choices, improve food enjoyment, as well as increase adequate food intake.11


Poor nutrition risk scores were associated with an increase in prevalence of LBP. Those with back pain were more likely to report poor appetite, oral problems, polypharmacy, and issues with ability to purchase healthy food options. Practitioners should pay special attention to the dietary history and nutritional assessments of those with LBP in this age range, as well as socio-economic issues that could have effects on the ability to make healthy choices.