Kidney Disease in Women is Associated with Disadvantaged Childhood Socioeconomic Position

Childhood modifiable risk factors and later life chronic kidney disease: a systematic review

BACKGROUND

Relationships between adulthood modifiable risk factors and chronic kidney disease (CKD) are well-established, but associations with childhood risk factors are unclear. This study systematically assesses the published evidence about childhood modifiable risk factors and adulthood CKD.

METHODS

We searched MEDLINE, EMBASE, and Web of Science to 6th May 2022. Articles were included if (1) they were population-based longitudinal studies, (2) exposures were potentially modifiable, for example through pharmacological or lifestyle modifications, including clinical conditions/measures (diabetes, blood pressure, adiposity, and dyslipidaemia); health behaviours (smoking, alcohol consumption, physical activity, fitness, and poor nutrition); and socio-economic factors (socio-economic position), and occurred during childhood (ages 2-19 years), and (3) outcome was CKD or surrogate markers of CKD in adulthood (ages 20 years or older). Three reviewers independently extracted the data.

RESULTS

15,232 articles were identified after deduplication; 17 articles met the inclusion criteria, reporting childhood blood pressure (n = 8), adiposity (n = 4), type 2 diabetes (n = 1), socio-economic position (n = 1), famine (n = 1), cardiorespiratory fitness (n = 1), and a healthy lifestyle score (n = 1). The results suggested positive associations of childhood adiposity, type 2 diabetes, and low socio-economic position and cardiorespiratory fitness in females with CKD in adulthood. Findings were inconsistent on associations between childhood BP and CKD in adulthood. Childhood healthy lifestyle score and exposure to famine were not associated with risk of CKD in adulthood.

CONCLUSIONS

The limited evidence suggests childhood factors may contribute to the CKD risk in adulthood, particularly adiposity, type 2 diabetes, and low socio-economic position and cardiorespiratory fitness in females. Further high-quality community-based studies are needed with long-term follow-up and investigation of a broader range of modifiable risk factors.

Where do you live and what do you do? Two questions that might impact your kidney health

In many cases the social determinants of health need to be assessed through their interaction with environmental factors. This review looks at the impact of physical location and occupation of individuals on their kidney health. It examines the effect of living at high altitude on kidney function and the relationship between extreme cold or hot temperatures and the incidence of kidney injury. It reviews as well the many occupations that have been linked to kidney disease in high-income and low-and-middle-income countries. As a conclusion, this overview proposes preventive recommendations that could be individualized based on weather, altitude, socio-economic level of the country and occupation of the individual.

Association between socioeconomic position and cystatin C in the Heinz Nixdorf Recall Study

Social inequalities in health and disease are well studied. Less information is available on inequalities in biomarker levels indicating subclinical stages of disease such as cystatin C, an early diagnostic marker of renal dysfunction and predictor for cardiovascular disease. We evaluated the relationship between cystatin C, socioeconomic position (SEP) and established cardiovascular risk factors in a population-based study. In 4475 men and women aged 45–75 years participating in the baseline examination of the Heinz Nixdorf Recall Study cystatin C was measured from serum samples with a nephelometric assay. SEP was assessed by education and household income. Linear regression models were used to analyse the association between SEP and cystatin C as well as the impact of cardiovascular risk factors (i.e., body mass index, blood pressure, blood glucose, diabetes mellitus, blood lipids, C-reactive protein, smoking) on this association. After adjustment for age and sex cystatin C decreased by 0.019 mg/l (95% confidence interval (CI) − 0.030 to − 0.008) per five years of education. While using a categorical education variable cystatin C presented 0.039 mg/l (95% CI 0.017–0.061) higher in men and women in the lowest educational category (≤ 10 years of education) compared to the highest category (≥ 18 years). Concerning income, cystatin C decreased by 0.014 mg/l (95% CI − 0.021 to − 0.006) per 1000 € after adjustment for age and sex. For men and women in the lowest income quartile cystatin C was 0.024 mg/l (95% CI 0.009–0.038) higher compared to the highest income quartile. After adjusting for established cardiovascular risk factors the observed associations were substantially diminished. Social inequalities seem to play a role in subclinical stages of renal dysfunction, which are also related to development of cardiovascular disease. Adjustment for traditional cardiovascular risk factors showed that these risk factors largely explain the association between SEP and cystatin C.

Comparison of smoking reduction with improvement of social conditions in early life: simulation in a British cohort

BACKGROUND

Health care evaluation models can be useful to assign different levels of priority to interventions or policies targeting different age groups or different determinants of health. We aimed to assess early mortality in counterfactual scenarios implying reduced adverse childhood experience (ACE) and/or improved educational attainment (childhood and early life characteristics), compared with a counterfactual scenario implying reduced smoking in adulthood.

METHODS

We used data from the 1958 National Child Development Study British birth cohort, which initially included 18 558 subjects. Applying a potential outcome approach, scenarios were simulated to estimate the expected mortality between ages 16 and 55 under a counterfactual decrease by half of the observed level of exposure to (i) ACE, (ii) low educational attainment (at age 22), (iii) ACE and low educational attainment (a combined exposure) and (iv) smoking at age 33. Estimations were obtained using g-computation, separately for men and women. Analyses were further stratified according to the parental level of education, to assess social inequalities.

RESULTS

The study population included 12 164 members. The estimated decrease in mortality in the counterfactual scenarios with reduced ACE and improved educational attainment was close to the decreased mortality in the counterfactual scenario with reduced smoking, showing a relative difference in mortality of respectively -7.2% [95% CI (confidence interval) = (-12.2% to 1.2%)] versus -7.0% (-13.1% to +1.2%) for women, and -9.9% (-15.6% to -6.2%) versus -12.3% (-17.0% to -5.9%) for men.

CONCLUSIONS

Our results highlight the potential value of targeting early social characteristics such as ACE and education, compared with well-recognized interventions on smoking.

Special Report: The Biology of Inequalities in Health: The Lifepath Consortium

Funded by the European Commission Horizon 2020 programme, the Lifepath research consortium aimed to investigate the effects of socioeconomic inequalities on the biology of healthy aging. The main research questions included the impact of inequalities on health, the role of behavioral and other risk factors, the underlying biological mechanisms, the efficacy of selected policies, and the general implications of our findings for theories and policies. The project adopted a life-course and comparative approach, considering lifetime effects from childhood and adulthood, and pooled data on up to 1.7 million participants of longitudinal cohort studies from Europe, USA, and Australia. These data showed that socioeconomic circumstances predicted mortality and functional decline as strongly as established risk factors currently targeted by global prevention programmes. Analyses also looked at socioeconomically patterned biological markers, allostatic load, and DNA methylation using richly phenotyped cohorts, unraveling their association with aging processes across the life-course. Lifepath studies suggest that socioeconomic circumstances are embedded in our biology from the outset—i.e., disadvantage influences biological systems from molecules to organs. Our findings have important implications for policy, suggesting that (a) intervening on unfavorable socioeconomic conditions is complementary and as important as targeting well-known risk factors, such as tobacco and alcohol consumption, low fruit and vegetable intake, obesity and a sedentary lifestyle, and that (b) effects of preventive interventions in early life integrate interventions in adulthood. The report has an executive summary that refers to the different sections of the main paper.

Special Report: The Biology of Inequalities in Health: The Lifepath Consortium

Funded by the European Commission Horizon 2020 programme, the Lifepath research consortium aimed to investigate the effects of socioeconomic inequalities on the biology of healthy aging. The main research questions included the impact of inequalities on health, the role of behavioral and other risk factors, the underlying biological mechanisms, the efficacy of selected policies, and the general implications of our findings for theories and policies. The project adopted a life-course and comparative approach, considering lifetime effects from childhood and adulthood, and pooled data on up to 1.7 million participants of longitudinal cohort studies from Europe, USA, and Australia. These data showed that socioeconomic circumstances predicted mortality and functional decline as strongly as established risk factors currently targeted by global prevention programmes. Analyses also looked at socioeconomically patterned biological markers, allostatic load, and DNA methylation using richly phenotyped cohorts, unraveling their association with aging processes across the life-course. Lifepath studies suggest that socioeconomic circumstances are embedded in our biology from the outset-i.e., disadvantage influences biological systems from molecules to organs. Our findings have important implications for policy, suggesting that (a) intervening on unfavorable socioeconomic conditions is complementary and as important as targeting well-known risk factors, such as tobacco and alcohol consumption, low fruit and vegetable intake, obesity and a sedentary lifestyle, and that (b) effects of preventive interventions in early life integrate interventions in adulthood. The report has an executive summary that refers to the different sections of the main paper.

Interpreting mutual adjustment for multiple indicators of socioeconomic position without committing mutual adjustment fallacies

Research into the effects of Socioeconomic Position (SEP) on health will sometimes compare effects from multiple, different measures of SEP in "mutually adjusted" regression models. Interpreting each effect estimate from such models equivalently as the "independent" effect of each measure may be misleading, a mutual adjustment (or Table 2) fallacy. We use directed acyclic graphs (DAGs) to explain how interpretation of such models rests on assumptions about the causal relationships between those various SEP measures. We use an example DAG whereby education leads to occupation and both determine income, and explain implications for the interpretation of mutually adjusted coefficients for these three SEP indicators. Under this DAG, the mutually adjusted coefficient for education will represent the direct effect of education, not mediated via occupation or income. The coefficient for occupation represents the direct effect of occupation, not mediated via income, or confounded by education. The coefficient for income represents the effect of income, after adjusting for confounding by education and occupation. Direct comparisons of mutually adjusted coefficients are not comparing like with like. A theoretical understanding of how SEP measures relate to each other can influence conclusions as to which measures of SEP are most important. Additionally, in some situations adjustment for confounding from more distal SEP measures (like education and occupation) may be sufficient to block unmeasured socioeconomic confounding, allowing for greater causal confidence in adjusted effect estimates for more proximal measures of SEP (like income).