Socioeconomic position and body composition across the life course: a systematic review protocol

INTRODUCTION: The relation between socioeconomic position (SEP) and obesity measured by body mass index (BMI) has been extensively reviewed, but there is less research on the association between SEP and body composition. Fat distribution and muscle quality have been linked to adverse health outcomes such as cardiovascular disease, diabetes and poor physical capability. There is some evidence of secular changes in body composition with increasing fat-mass and reducing muscle quantity and strength, but it is unclear whether there have been secular changes in social inequalities in body composition. The aim is to perform a systematic review of the existing literature on the association between SEP and body composition and to explore any secular changes. METHODS: The systematic review will be carried out according to PRISMA guidelines. An electronic search of MEDLINE and Embase Classic + Embase will be conducted using OvidSP as the database interface, as well as SPORTDiscus using EBSCO. Two independently working reviewers will initially screen abstracts to exclude papers that are clearly ineligible, followed by a full-text screening to exclude papers not meeting all inclusion criteria. Any disagreements will be resolved through discussion. Data extraction and quality assessment of eligible papers will be carried out by 2 reviewers using a standardised form. The reference lists of identified papers will be searched for additional papers. Original studies in the English language, which examine the association between SEP at any age and body composition at the same or later age will be included if they use any recognised measures of SEP (e.g. income, occupation, over-crowding) and a recognised measure of body composition (total, proportional or location of fat mass and fat-free mass, using any appropriate methods, excluding anthropometry). Due to expected heterogeneity, a narrative synthesis is expected, with a descriptive summary to be provided in tables. If there is consistency in reporting of associations, a random-effects meta-analysis will be used to provide an overall summary estimate. DISCUSSION: The results of the review will summarise the existing evidence on social inequalities in body composition. Findings will identify gaps in knowledge and where further research is required. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019119937

Life course socioeconomic position and body composition in adulthood: a systematic review and narrative synthesis

INTRODUCTION: Multiple systematic reviews have investigated the relation between socioeconomic position (SEP) and body mass index (BMI) throughout the life course. However, BMI does not capture quantity and distribution of fat and muscle, which are better indicators of obesity than BMI, and have been independently linked to adverse health outcomes. Less is known about the relation between SEP and body composition, and the literature has not been reviewed. We therefore systematically reviewed the literature on the association between life course SEP and body composition in adulthood. METHODS: A protocol was registered on PROSPERO (CRD42019119937), and the review followed PRISMA guidelines. An electronic search of three databases (MEDLINE, Embase Classic + Embase and SPORTDiscus) was conducted. Original studies in the English language were included that examine the association between any recognised measure of SEP at any age and body composition (fat mass, fat-free mass, ratio and distribution) in adulthood, measured using a direct technique, i.e., not an anthropometric measure. A narrative synthesis was conducted. RESULTS: A total of 47 papers were included in the final review, none were from low-income countries (LICs). Greater advantage in childhood and adulthood was associated with lower fat levels in high-income countries (HICs). Associations in the opposite direction were found exclusively in middle-income countries (MICs). No studies in MICs reported associations for childhood SEP. For measures of lean mass, the majority of papers reported no association, or greater advantage in adulthood associated with higher lean mass, with little variation between HICs and MICs. Associations in HICs are more often observed in women than men. CONCLUSION: The results indicate that fat measures follow similar patterns to those seen for BMI, and that women in HICs are more likely to experience inequalities in both fat and lean measures. Further research in LICs and MICs is needed

Socioeconomic position and body composition in childhood in high- and middle-income countries: a systematic review and narrative synthesis

BACKGROUND: The relation between socioeconomic position (SEP) and obesity measured by body mass index (BMI), a measure of weight for height, has been extensively reviewed in children, showing consistent associations between disadvantaged SEP and higher BMI in high-income countries (HICs) and lower BMI in middle-income countries (MICs). Fat mass (FM), a more accurate measure of adiposity, and fat-free mass (FFM) are not captured by BMI, but have been shown to track from childhood to adulthood, and be important for cardiovascular health and functional outcomes in later life. It is not clear whether body composition is associated with SEP. We systematically reviewed the association between SEP and body composition in childhood. METHODS: A systematic review was carried out following PRISMA guidelines. The protocol was pre-registered with PROSPERO (CRD42019119937). Original studies in the English language, which examined the association between SEP and body composition in childhood, were included. An electronic search of three databases was conducted. Two independent reviewers carried out screening, data extraction and quality assessment. Due to heterogeneity in results, a narrative synthesis was conducted. Heterogeneity in findings according to SEP, sex, body composition measure and country income level was investigated. RESULTS: 50 papers were included, the majority from HICs. No papers were from low-income countries. Disadvantage in childhood was associated with greater FM and lower FFM in HICs, but with lower FM and lower FFM in MICs. When measures of FFM indexed to height were used there was no evidence of associations with SEP. In HICs, more studies reported associations between disadvantaged SEP and higher FM among girls comparative to boys. CONCLUSIONS: Inequalities in FM are evident in HICs and, in the opposite direction, in MICs and follow similar trends to inequalities for BMI. Inequalities in height are likely important in understanding inequalities in FFM

Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

BACKGROUND: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. METHODS: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. FINDINGS: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. INTERPRETATION: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. FUNDING: LSHTM COVID-19 Response Grant (DONAT15912)