Changes in Body Mass Index on the Risk of Back Pain: Estimating the Impacts of Weight Gain and Loss

Abstract

Background The relationship between obesity and back pain in older populations is poorly understood. This study aimed to examine (1) the impacts of changes in obesity status on back pain risk and (2) the heterogeneity in the influence of changes in obesity status according to muscle strength. Methods We analyzed 6,868 participants in waves 4 (2008–2009), 6 (2012–2013), and 7 (2014–2015) of the English Longitudinal Study of Ageing. The exposure comprised continuous body mass index (BMI) values, whereas the outcome comprised self-reported moderate or severe back pain. The targeted minimum loss-based estimator was used to estimate the impacts of hypothetical changes in BMI in each wave under 10 scenarios encompassing a 5%−25% hypothetical reduction/increase in BMI. We also performed stratified analysis using handgrip strength at the baseline. Results For the hypothetical reduction scenarios, a 10% (relative risk [RR]) (95% confidence interval [CI]) = 0.82 (0.73–0.92), P = 0.001] reduction in BMI estimated a significantly lower back pain risk compared to the observed data. For the hypothetical increase scenarios, a 5% [RR (95% CI) = 1.11 (1.04–1.19), P = 0.002] increase in BMI estimated a significantly higher back pain risk. Increased BMI had a higher risk of back pain among those with weak strength when stratified by handgrip strength but not among those with strong strength. Conclusions Our study confirmed that weight gain leads to a greater risk of back pain as well as heterogeneity in the influence of changes in obesity status according to the handgrip strength.

Rapid weight change as a predictor of disability among community‐dwelling Japanese older adults

“…Further, the effect of weight gain on comorbidities of motor functions should not be ignored, 44,45 as it leads to comorbidities such as joint diseases, osteoarthritis, and lower back pain. In particular, lower‐extremity mobility such as walking, stair climbing, and chair rise ability, worsens with increasing weight gain in older adults 46,47 .…”

“…Smoking cessation and increased physical activity not only reduce the risk of future disability but also activate nitric oxide, decrease reactive oxygen species, and reduce the risks of VED and inflammation. 42,43 Further, the effect of weight gain on comorbidities of motor functions should not be ignored, 44,45 as it leads to comorbidities such as joint diseases, osteoarthritis, and lower back pain. In particular, lower-extremity mobility such as walking, stair climbing, and chair rise ability, worsens with increasing weight gain in older adults.…”

Assessing the impacts of smoking cessation and resumption on back pain risk in later life

“…The following variables assessed in wave 4 were used as covariates: sex (U.S. Department of Health and Human Services, 2020; Fancourt & Steptoe, 2018), race (U.S. Department of Health and Human Services, 2020; Fancourt & Steptoe, 2018), duration of education (Ikeda et al, 2019, 2021; Ikeda, Matsuyama, Murakami, & Osaka, 2022), age (U.S. Department of Health and Human Services, 2020; Ikeda et al, 2019, 2021), marital status (U.S. Department of Health and Human Services, 2020; Ikeda et al, 2019, 2021), equalized household income (U.S. Department of Health and Human Services, 2020; Ikeda et al, 2019, 2021), weekly engagement in mild, moderate or vigorous physical activity (Chiolero et al, 2008; Ikeda, Cooray, Murakami, & Osaka, 2022), lung disease diagnosis (Thomson, 2004), asthma diagnosis (Thomson, 2004), osteoporosis diagnosis (Glassman et al, 2000), cancer diagnosis (U.S. Department of Health and Human Services, 2020), depressive symptoms (Ikeda et al, 2019; Murphy et al, 2003), handgrip strength (Ikeda, Cooray, Suzuki, et al, 2022; Kojima et al, 2015), body mass index (Dare et al, 2015; Ikeda, Cooray, Suzuki, et al, 2022) and back pain and its intensity. Furthermore, the following time‐varying variables assessed in wave 6 were used as covariates: age; marital status; equalized household income; participation in mild, moderate or vigorous physical activity on a weekly basis; diagnosis of lung disease, asthma, osteoporosis and cancer; depressive symptoms; handgrip strength; body mass index; and back pain and its intensity.…”

“…Body mass index was calculated as body weight (kg) divided by the square of height (m), and it was measured by trained nurses. Furthermore, both handgrip strength and body mass index were included in our model because a previous study reported the heterogeneity in the impacts of changes in obesity status on back pain according to muscle strength (Ikeda, Cooray, Suzuki, et al, 2022). We used back pain and its intensity assessed at waves 4 and 6 as covariates for the following reasons.…”

Effect of Tooth Loss on Cognitive Function among Older Adults in Singapore

“…The longitudinal modified treatment policy (LMTP) approach is a recently developed nonparametric alternative that can be used to define causal research questions and estimate relevant statistical parameters flexibly using observational data. Causal effects are defined by shifting the exposure as a deterministic function of the observed level of exposure (Díaz et al 2021; Ikeda et al 2022; Nugent and Balzer 2023).…”