Birth Weight, Cardiovascular Health, and Microvascular Complications in Individuals with Diabetes Mellitus
Article information
Abstract
Background
Diabetes often leads to microvascular complications, including nephropathy, neuropathy, and retinopathy. Understanding the impact of early-life factors like birth weight and modifiable behaviors such as cardiovascular health (CVH) is essential for preventing these complications.
Methods
We included 11,515 participants with diabetes but without microvascular complications at baseline from the UK Biobank Study. CVH was evaluated using the Life’s Essential 8 score. Independent and joint associations of birth weight and CVH with microvascular complications were analyzed using Cox proportional hazard models. Two-sample Mendelian randomization (MR) analyses estimated unconfounded associations between birth weight and microvascular complications.
Results
Over a median follow-up of 13.1 years, 3,010 microvascular complications occurred. Compared with normal birth weight (2.5–4.0 kg), low birth weight (LBW; <2.5 kg) was associated with 15% higher risk of diabetic nephropathy (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.01 to 1.31), but not with neuropathy and retinopathy. High birth weight (>4.0 kg) was not associated with the risk of diabetic microvascular complications. MR analysis confirmed the association between LBW and nephropathy. Adherence to high CVH was associated with a reduced risk of microvascular complications compared to low CVH, regardless of birth weight. The HRs were 0.70 (95% CI, 0.59 to 0.84) for the LBW group and 0.74 (95% CI, 0.68 to 0.80) for the group with birth weight ≥2.5 kg (P for interaction=0.69).
Conclusion
LBW was an independent risk factor for nephropathy among diabetic patients. However, the detrimental effects of LBW might be mitigated by improvement in CVH.
Highlights
• Low birth weight is associated with an increased risk of diabetic nephropathy.
• MR analyses support a causal link between birth weight and diabetic nephropathy.
• Improved cardiovascular health may mitigate the adverse effects of low birth weight.
INTRODUCTION
Diabetes mellitus is a major global health challenge, with its prevalence steadily increasing, leading to significant morbidity and mortality worldwide [1]. One of the most debilitating consequences of diabetes is the development of microvascular complications, including diabetic nephropathy, neuropathy, and retinopathy [2-5] These complications not only diminish the quality of life but also contribute to the escalating healthcare costs associated with the management of diabetes. Therefore, understanding the factors that contribute to the risk of these complications is crucial for developing effective prevention and treatment strategies.
Birth weight, an indicator of intrauterine growth, has been recognized as an important early-life factor that may influence the development of cardiometabolic diseases later in life [6]. Previous studies have suggested that low birth weight (LBW) or fetal exposure to severe malnutrition was associated with an increased risk of developing various health conditions [7-10]. However, the relationship between birth weight and the risk of diabetic microvascular complications remains controversial, with inconsistent findings reported across different studies. These discrepancies may be attributed to variations in study design, sample size, population characteristics, and the presence of confounding factors [11-17].
In addition to birth weight, cardiovascular health (CVH) is another critical factor that influences the progression of diabetic complications. The American Heart Association’s Life’s Essential 8 (LE8) score is a comprehensive metric that encompasses key lifestyle and health factors, including diet, physical activity, smoking status, sleep health, body mass index, blood lipids, blood glucose, and blood pressure [18]. A high level of CVH has been associated with a reduced risk of cardiovascular diseases and longer life expectancy [19-23]. However, the interaction between birth weight and CVH in determining the risk of diabetic microvascular complications has not been thoroughly investigated.
In this study, we aimed to explore the independent and joint associations of birth weight and CVH with the risk of developing diabetic microvascular complications in a large, well-characterized cohort of diabetic patients. By leveraging both observational and Mendelian randomization (MR) analyses, we seek to clarify the potential causal relationships and provide new insights into the early-life and modifiable factors that may contribute to the prevention and management of diabetic microvascular complications.
METHODS
Study design and population of observational study
The United Kingdom Biobank (UKB) is a well-characterized prospective cohort study comprising more than 500,000 participants aged 40 to 69 years recruited from 22 centers across the UK between 2006 and 2010 [24]. In this study, our analyses were restricted to participants with prevalent diabetes at baseline, who were identified if their onset time of diabetes was earlier than the date of attending the assessment center. We identified cases of diabetes through the hospital registration records, self-reported diagnoses by physicians (except for gestational diabetes), and either a random glucose level ≥11.1 mmol/L or a glycosylated hemoglobin (HbA1c) level ≥48 mmol/mol (6.5%) as per the criteria established by American Diabetes Association (Supplementary Table 1) [25]. We further excluded participants with unknown birth weight, or with diagnosed diabetic nephropathy, diabetic neuropathy, or diabetic retinopathy at baseline. Prevalent diabetic microvascular complications at baseline were identified using a combination of self-reported diagnoses and prior hospital admission records. The specific International Classification of Diseases (ICD) codes used to define each complication are detailed in Supplementary Table 1. A total of 11,515 participants were included in the analysis (Fig. 1). The UKB study received approval from the Northwest Multi-center Research Ethics Committee (21/NW/0157), and all participants provided written informed consent.
Study design for observational study and Mendelian randomization study. EGG, early growth genetics; SNP, single nucleotide polymorphism.
Assessment of birth weight, CVH, and covariates
Participants were asked to report their birth weight in either kilogram (kg) or imperial pounds and ounces which was subsequently converted into kg. The validity of self-reported birth weight in the UKB has been confirmed in prior studies [26]. According to the World Health Organization criteria, a birth weight between 2.5 and 4.0 kg was categorized as normal, <2.5 kg as low, and >4 kg as high [27].
We assessed CVH using the LE8 score, which comprises eight components including diet, physical activity, nicotine exposure, sleep health, BMI, blood lipids, blood glucose, and blood pressure [18]. In the UKB, data for these components were collected at baseline to compute the overall CVH score. Detailed scoring algorithm for CVH assessment is shown in Supplementary Table 2. Each CVH component was assigned a score ranging from 0 to 100 points according to the LE8 recommendation. Overall CVH was evaluated by the unweighted average score of all eight components, ranging from 0 to 100 points.
Data on following covariates were collected and adjusted for in statistical analyses to control for confounding effects. Information on age, sex, ethnicity, education, dietary habits, physical activity, smoking status, sleep duration, and medication use were self-reported at baseline. The dietary quality was assessed using the Dietary Approaches to Stop Hypertension (DASH) score based on the collected dietary data (Supplementary Table 3) [28]. Multiple deprivation index (MDI) was calculated based on participants’ postcode with a higher score indicating a higher degree of deprivation. Diabetes duration for each participant was calculated as the years between the first occurrence of diabetes and baseline assessment and assigned as 0 for those free of diabetes at baseline.
Ascertainment of diabetic microvascular complications
The primary outcome of this study was the incidence of diabetic microvascular complications including diabetic neuropathy, nephropathy, and retinopathy. The diagnoses of outcomes were defined based on the linked hospital admissions and mortality data according to the ICD codes, ninth and tenth revision (Supplementary Table 1). Participants were followed up until the first occurrence of any of the three diabetic microvascular complications, death, loss to follow-up, or the end of the follow-up period on December 19, 2022, whichever occurred first.
Statistical analysis
Multivariable Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations of LBW and high birth weight (HBW) with incident diabetic microvascular complications with normal birth weight (NBW) as reference. In these models, we adjusted for age (continuous), sex (men or women), ethnicity (white or non-white), education (≥ or <college/university degree), MDI (continuous), smoking status (never, previous, or current), physical activity (active or non-active), sleep duration (<7, 7–9, or ≥9 hours/day), dietary quality score (continuous), diabetes medication (use insulin or not), and diabetes duration (continuous). We imputed missing values using the median for continuous covariates and mode for categorical covariates. The robustness of our findings was examined by two sensitivity analyses using another method (random forest) to impute missing data and censoring follow-up on 31 December 2019 to avoid the potential bias caused by the pandemic of coronavirus disease 2019 (COVID-19).
We examined the shape of the relationship between birth weight and diabetic microvascular complications by treating birth weight as a continuous variable and including a restricted cubic spline term for birth weight with three knots at the 10th, 50th, and 90th centiles in the Cox full model. The non-linearity P value was calculated with a likelihood ratio test by comparing the models with and without the cubic spline term.
A stratified analysis was conducted to assess whether the association between CVH and the risk of diabetic microvascular complications varied by birth weight (<2.5 or ≥2.5 kg). CVH was dichotomized into two categories: low CVH (LE8 score <median) and high CVH (LE8 score ≥median), with low CVH serving as the reference group. Cox proportional hazards models were used to estimate the associations, adjusting for age, sex, ethnicity, education, MDI, insulin use, and diabetes duration. The multiplicative interaction between birth weight and CVH was assessed by adding a product term in the multivariable Cox models. We used R version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria) for analyses and calculated 95% CI and two-sided P values for statistical inference.
Two-sample Mendelian randomization analyses
Genetic instrumental variables for birth weight were obtained from a recent European ancestry genome-wide association study (GWAS) meta-analysis of birth weight [29], which partitioned genetic effects on birth weight into fetal and maternal components. We extracted genome-wide significant (P<5×10–8) uncorrelated (r2<0.001) variants as instrumental variables for overall birth weight (155 single nucleotide polymorphisms [SNPs]) and birth weight determined by fetal genome only (25 SNPs). Genetic association estimates for diabetic nephropathy, neuropathy, and retinopathy were extracted from GWAS summary statistics in FinnGen study (Fig. 1) [30].
Summarized data on genetic associations with exposures and outcomes were harmonized to ensure that the selected variants were coded from the same strand. For palindromic SNPs, the effect alleles were inferred based on allele frequency information, in case where this was not feasible, the SNP was excluded. Only SNPs with gene-exposure and gene-outcome association summary data were used in the MR analysis. After harmonization, 145 SNPs for overall birth weight and 25 SNPs for birth weight directly determined by fetal genome were included in the following MR analyses. F statistics were 57 for the 145 SNPs and 62 for the 25 SNPs, which are far greater than 10, supporting the reliability of the genetic instrumental variables.
The inverse-variance weighted method was used as the primary MR analysis approach, supplemented by sensitivity analyses using the MR-Egger [31], MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) [32], weighted median [33], and weighted mode [34] methods to assess the robustness of the findings. The leave-one-out and scatter plots were performed to assess the robustness of findings and exploring influential outliers. These MR analyses were performed using the ‘Two-Sample MR’ package in R [35].
RESULTS
Characteristics of participants
A total of 11,515 participants with diabetes but without diabetic microvascular complications at baseline were included in this study, of whom 55.0% were men, 94.2% were White, the mean age was 58.7 years, 14.6% took insulin, the mean duration of diabetes until baseline was 4.0 years, 15.0% had LBW, and 13.2% had HBW (Table 1).
Baseline characteristics according to birth weight categories among 11,515 diabetic patients in the UKB
Associations between birth weight and incident diabetic microvascular complications among diabetic patients
During a median follow-up of 13.1 years, 3,010 incident diabetic microvascular complications were identified, including 1,667 diabetic nephropathy events, 559 diabetic neuropathy events, and 1,516 diabetic retinopathy events. Compared with diabetes patients with NBW, those with LBW had 10% higher risk of diabetic microvascular complications (multivariable-adjusted HR, 1.10; 95% CI, 1.00 to 1.21), however, those with HBW had comparable risk.
Analyses for individual diabetic microvascular complication indicated that, compared with NBW, LBW was associated with an increased risk of diabetic nephropathy (HR, 1.15; 95% CI, 1.01 to 1.31), but not with neuropathy and retinopathy. In contrast, HBW was associated with a lower risk of diabetic retinopathy (HR, 0.81; 95% CI, 0.69 to 0.96), but not with nephropathy and retinopathy (Table 2). Restricted cubic spline analyses further confirmed the association of LBW with an increased risk of diabetic nephropathy (P for overall=0.02 and P for nonlinear=0.02) (Fig. 2).
Hazard ratios (95% CI) of incident microvascular complications according to birth weight categories among 11,515 diabetic patients in the UKB
Associations of birth weight with risks of (A) diabetic microvascular complication, (B) diabetic nephropathy, (C) diabetic neuropathy, and (D) diabetic retinopthy among 11,515 diabetic patients in the United Kingdom Biobank. Cox proportional hazards models were used for analysis, including restricted cubic spline term for birth weight, with adjustment for age, sex, ethnicity (white or non-white), education (≥college/university degree or not), multi-deprivation index, dietary sore, smoking status (never, previous, or current), moderate or vigorous physical activity (metabolic equivalent of task minutes per week), sleeping duration (<7, 7–9, or ≥9 hours per day), usage of insulin (yes or no), and diabetic duration. CI, confidence interval.
Sensitivity analyses using random forest to impute missing data and censoring follow-up on December 31, 2019 (before the pandemic of COVID) showed consistent results (Supplemental Tables 4 and 5).
MR-based analysis of associations between birth weight and diabetic microvascular complications
The two-sample MR analyses for overall birth weight showed that higher genetically-predicted birth weight was associated with a lower risk of diabetic nephropathy (odds ratio [OR], 0.66; 95% CI, 0.50 to 0.89) and diabetic retinopathy (OR, 0.69; 95% CI, 0.57 to 0.85), while no significant association was observed between birth weight and diabetic neuropathy. For birth weight directly determined by fetal genome only, higher genetically-predicted birth weight remained associated with lower risks of diabetic nephropathy (OR, 0.57; 95% CI, 0.35 to 0.91) and diabetic retinopathy (OR, 0.54; 95% CI, 0.35 to 0.82). These results suggest that the observed association of LBW with an increased risk of nephropathy and HBW with a decreased risk of retinopathy may not be biased by residual confounding factors.
Sensitivity analyses using MR-Egger, weighted median, weighted mode, and MR-PRESSO confirmed the robustness of these findings (Fig. 3, Supplementary Table 6, Supplementary Figs. 1-12).
Two-sample Mendelian randomization (MR)-based analysis of associations of overall birth weight (A) and birth weight determined by fetal genome only (B) with risks of diabetic microvascular complications. SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; IVW, inverse-variance weighted; PRESSO, pleiotropy residual sum and outlier.
Association between CVH and risks of diabetic microvascular complications stratified by birth weight
Given that higher CVH was associated with lower risk of diabetic microvascular complications (Supplementary Table 7, Supplementary Fig. 13), we further conducted stratification analysis to examine if the relation between CVH and risk of diabetic microvascular complications was modified by birth weight. Compared with participants with low CVH, those with high CVH had a 30% lower risk of composite microvascular complications (HR, 0.70; 95% CI, 0.59 to 0.84) in the LBW stratum and an 26% lower risk (HR, 0.74; 95% CI, 0.68 to 0.80) in the stratum of birth weight ≥2.5 kg (P for interaction=0.69) (Table 3).
Stratification analysis of associations of cardiovascular health with risks of microvascular complications according to birth weight among 11,515 diabetic patients in the UKB
DISCUSSION
In this large prospective cohort study, we examined the association between birth weight and the risks of diabetic microvascular complications among diabetic patients. Among the three microvascular complications, LBW was linked to a higher risk of diabetic nephropathy, but not neuropathy or retinopathy. The causality of the inverse associations between LBW and risk of diabetic nephropathy was confirmed by MR analyses. Furthermore, we found no evidence of interactions between birth weight and CVH, indicating that higher levels of CVH in adulthood was associated with a lower risk of all three diabetic microvascular complications regardless of birth weight.
The associations between birth weight and risks of diabetic microvascular complications remain debatable. A longitudinal study including 308 Pima Indian type 2 diabetes mellitus (T2DM) patients revealed a higher prevalence of albuminuria among those with LBW compared to those with NBW [13]. A case-control study including 184 Caucasian insulin-dependent diabetic patients with nephropathy and 182 patients without nephropathy reported similar results in women [11]. However, a cross-sectional study including 1,543 Caucasian diabetic patients and a case-control study including 51 Danish diabetic subjects with diabetic nephropathy and 51 matched controls showed non-significant associations between birth weight and risk of diabetic nephropathy [12,17]. With the well-characterized cohort design, large sample size, and long follow-up duration in the UKB, our current study robustly indicated an increased risk of diabetic nephropathy associated with LBW among diabetic patients.
The association between birth weight and diabetic neuropathy has not been well studied previously. Results from the population-based Gutenberg Health Study showed that both LBW and HBW were related to a higher risk of diabetic retinopathy among 402 diabetic patients [15]. In contrast, the Atherosclerosis Risk in Communities Study including 609 adults with T2DM and a cross-sectional study including 1,543 Finnish patients with type 1 diabetes mellitus reported no association between birth weight and diabetic retinopathy [16,17]. In our study, we observed a significant association between HBW and lower incident diabetic retinopathy.
These observational findings may be subject to residual confounders or reverse causation, although we have adjusted for known confounders in the models. To overcome this limitation, we further conducted MR-based analyses to confirm the causality of these associations. Recent studies have attempted to utilize MR analysis to explore the association between birth weight and diabetes as well as cardiovascular diseases, aiming to address the Developmental Origins of Health and Disease (DOHaD) hypothesis [36,37]. However, these MR analyses neglected the potential effect of maternal genomes that could serve as proxies for the intrauterine environment [36]. Warrington et al. successfully developed a structural equation model to partition genetic effects on birth weight into maternal and fetal components [29]. By utilizing these identified SNPs, we found that even after accounting for the potential influence of the intrauterine environment, birth weight still has independent associations with risk of diabetic nephropathy and retinopathy. From a clinical perspective, our study suggests that LBW represents an independent risk factor for the development of nephropathy in diabetic patients. This encourages early targeted risk stratification, more positive preventive strategies, and early intervention in this high-risk population.
The differential associations between birth weight and diabetic microvascular complications, specifically nephropathy, retinopathy, and neuropathy, may be attributed to differences in the underlying pathophysiological mechanisms and organ-specific vulnerabilities during fetal development. For diabetic nephropathy, evidence suggests that LBW is linked to reduced nephron endowment due to impaired kidney development during fetal growth [38-40]. This ‘nephron deficit’ hypothesis proposes that fewer nephrons result in compensatory hyperfiltration, increasing the long-term susceptibility to kidney damage, particularly in the context of diabetes. For diabetic retinopathy, the observed association with HBW may be explained by fetal overnutrition or maternal hyperglycemia during pregnancy, which can affect retinal vascular development. Prior studies have reported that excessive fetal growth may alter retinal microvascular structure, potentially influencing the risk of retinopathy later in life [41]. However, the exact mechanisms remain less clear and warrant further investigation. For diabetic neuropathy, no significant association with birth weight was observed in our study. Unlike the kidney and retina, the peripheral nervous system may be less directly influenced by early-life growth patterns. Neuropathy is typically linked to chronic hyperglycemia, oxidative stress, and advanced glycation end products [42,43], which may override any subtle developmental effects related to birth weight.
After the release of LE8 in 2022, subsequent studies have demonstrated that higher CVH evaluated according to LE8 was associated with lower risks of CVDs and longer life expectancy [19-23]. Our study further showed that a high level of CVH, defined by LE8, was associated with a decreased risk of diabetic microvascular complications among diabetic patients, which is consistent with previous studies [44]. Differences in CVH susceptibility associated with birth weight may act as potential mediators in the associations between birth weight and diabetic microvascular complications. However, our analysis revealed that higher CVH was consistently associated with a lower risk of diabetic microvascular complications, regardless of birth weight. Moreover, no significant interaction was observed between birth weight and CVH in relation to microvascular complications, suggesting that the associations of birth weight and CVH with these outcomes may operate through independent pathways. These findings indicated that maintaining a high level of CVH would be beneficial for the prevention of microvascular complications among diabetic patients, irrespective of their birth weight.
Our study has several strengths that enhance the validity of the findings. First, the prospective cohort design, large sample size, and long follow-up duration enabled a robust exploration of the independent and joint associations of birth weight and CVH with incident microvascular complications among diabetic patients with sufficient statistical power. Second, the use of MR mitigates the potential influence of challenging-to-measure confounders that might bias the associations between birth weight and diabetic microvascular complications.
Nevertheless, several limitations should be kept in mind when interpreting our findings. First, the participants in the UKB were primarily of white ethnicity, which limits the generalizability of findings to other populations. Second, birth weight was self-reported by the participants, which introduces the possibility of recall bias. Third, CVH was evaluated at baseline in this study, providing a cross-sectional snapshot rather than longitudinal trajectories. Fourth, certain diabetes and non-diabetes medications, such as glucose-lowering agents (e.g., sodium glucose cotransporter 2 [SGLT2] inhibitors, glucagon like peptide-1 [GLP-1] receptor agonists), antihypertensive drugs (e.g., angiotensin-converting enzyme [ACE] inhibitors, angiotensin II receptor blocker [ARB]), and lipid-lowering agents (e.g., statins), may influence the risk of diabetic nephropathy. While the CVH metrics account for blood glucose, lipids, and blood pressure, they do not consider the specific medications used to manage these factors. This limitation highlights the need for future research to better understand the potential impact of medication use on diabetic nephropathy risk. Fifth, the inverse association observed in our MR analysis suggests that lower birth weight may be causally linked to a higher risk of nephropathy. This inference is supported by the use of genetic variants as instrumental variables, which are less susceptible to confounding and reverse causation compared to observational analyses. However, it is important to recognize that MR estimates reflect the lifelong cumulative effects of birth weight rather than the influence of birth weight at a specific developmental stage. Sixth, we cannot exclude the contribution of paternal genome on diabetes microvascular complications in the MR analyses. Lastly, due to the lack of individual-level data in two-sample MR analysis, we were unable to calculate discrepancy between genetically predicted and actual birth weight, preventing us from investigating its potential association with the risk of diabetic microvascular complications.
In conclusion, our findings indicate that LBW is an independent risk factor for diabetic nephropathy. Additionally, maintaining a high level of CVH is associated with reduced risks of diabetic microvascular complications, irrespective of birth weight. These results underscore the importance of recognizing LBW as a key indicator for identifying individuals at high-risk for diabetic nephropathy, thereby enabling tailored early prevention and intervention strategies.
SUPPLEMENTARY MATERIALS
Supplementary materials related to this article can be found online at https://doi.org/10.4093/dmj.2024.0518.
Definitions and field codes used for the identification of diabetes and diabetic microvascular complications in the UKB
Measurement and quantitative assessment of cardiovascular health according to the criteria of Life’s Essential 8
Dietary assessment in the United Kingdom Biobank
Hazard ratios (95% CI) of incident microvascular complications according to birth weight among 11,515 diabetic patients in the UKB with random forest to impute missing data
Hazard ratios (95% CI) of incident microvascular complications according to birth weight among 11,515 diabetic patients in the UKB with follow-up censored on 31 December 2019 to avoid the potential bias caused by the pandemic of COVID-19
Associations of genetically determined birth weight (overall, fetal-only effect) with diabetic microvascular complications
Hazard ratios (95% CI) of incident microvascular complications according to CVH among 11,515 diabetic patients in the UKB
Leave-one-out plot demonstrating influential outliers in Mendelian randomization (MR) analysis of overall birth weight and diabetic nephropathy.
Scatter plot demonstrating influential outliers in Mendelian randomization (MR) analysis of overall birth weight and diabetic nephropathy. SNP, single nucleotide polymorphism.
Leave-one-out plot demonstrating influential outliers in Mendelian randomization (MR) analysis of overall birth weight and diabetic neuropathy.
Scatter plot demonstrating influential outliers in Mendelian randomization (MR) analysis of overall birth weight and diabetic neuropathy. SNP, single nucleotide polymorphism.
Leave-one-out plot demonstrating influential outliers in Mendelian randomization (MR) analysis of overall birth weight and diabetic retinopathy.
Scatter plot demonstrating influential outliers in Mendelian randomization (MR) analysis of overall birth weight and diabetic retinopathy. SNP, single nucleotide polymorphism.
Leave-one-out plot demonstrating influential outliers in Mendelian randomization (MR) analysis of birth weight determined by fetal genome only and diabetic nephropathy.
Scatter plot demonstrating influential outliers in Mendelian randomization (MR) analysis of birth weight determined by fetal genome only and diabetic nephropathy. SNP, single nucleotide polymorphism.
Leave-one-out plot demonstrating influential outliers in Mendelian randomization (MR) analysis of birth weight determined by fetal genome only and diabetic neuropathy.
Scatter plot demonstrating influential outliers in Mendelian randomization (MR) analysis of birth weight determined by fetal genome only and diabetic neuropathy. SNP, single nucleotide polymorphism.
Leave-one-out plot demonstrating influential outliers in Mendelian randomization (MR) analysis of birth weight determined by fetal genome only and diabetic retinopathy.
Scatter plot demonstrating influential outliers in Mendelian randomization (MR) analysis of birth weight determined by fetal genome only and diabetic retinopathy. SNP, single nucleotide polymorphism.
Associations between cardiovascular health (CVH) and risk of diabetic microvascular complications among 11,515 diabetic patients in the United Kingdom Biobank. Cox proportional hazards models were used for analysis, including restricted cubic spline term for birth weight, with adjustment for age, sex, ethnicity (white or non-white), education (≥college/university degree or not), multi-deprivation index, dietary sore, smoking status (never, previous, or current), moderate or vigorous physical activity (metabolic equivalent of task minutes per week), sleeping duration (<7, 7–9, or ≥9 hours per day), usage of insulin (yes or no), and diabetic duration.
Notes
CONFLICTS OF INTEREST
No potential conflict of interest relevant to this article was reported.
AUTHOR CONTRIBUTIONS
Conception or design: H.G., J.L.
Acquisition, analysis, or interpretation of data: C.Y., A.F., X.Z., L.D.
Drafting the work or revising: C.Y., A.F., S.C., J.L.
Final approval of the manuscript: all authors.
FUNDING
Jie Li was supported by the National Natural Science Foundation of China (82473620, 82073528, 81673156, and 81302417). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
ACKNOWLEDGMENTS
The authors would like to express their sincere gratitude to all the participants and staff of the UK Biobank for their dedication and contribution to the research.