data sources
NHANES, an ongoing cross-sectional study conducted by the National Center for Health Statistics (NCHS), is a national database containing information about the health and nutritional status of adults and children in the United States. NHANES has been collecting data since 1999, including unique information on interviews and medical examinations. State department of health and human services (HHS) official website (http://www.cdc.gov/nchs/nhanes/nannes_quemplairees.htm) provides data are analyzed and illustrated. The NHANES protocol was approved by the NCHS Research Ethics Review Board, and informed consent was obtained from all participants. The NHANES database consists of five main components, including demographic data, dietary data, examination data, laboratory data, and questionnaire data. More detailed information about NHANES is available on the official website.
Participant selection
We conducted a series of data analyses based on data from two consecutive NHANES survey cycles: 1999-2000 and 2001-2002. After screening for a variety of conditions, we finally selected 21,004 (1999-2000:9,965 cases;2001-2002:11,039 cases) and 2,427 participants were selected for the final data analysis. Participants were screened based on the following exclusion criteria :(1) persons under 18 years of age (n=10,151);(2) Subjects with no telomere data (n=3026);(3) Subjects without insulin data (n=3200);(4) Some other data loss (n=2200).(Figure 1.) This study was not a clinical trial, so no clinical registration was required. The study procedure is in line with the World Medical Association's Helsinki Declaration (see the NHANES website for details).
Data Collection
All information is collected by uniformly trained investigators. These data include demographic data (gender, age, race/ethnicity, etc.), health-related behaviors (smoking and alcohol consumption), anthropometric measurements (e.g., height, waist circumference, weight, etc.) and biochemical tests (TC, TG, GLU, etc.).AIA- PACK method was used to determine insulin on TOSOH AIA system analyzer. The subjects' height, weight, and waist circumference were measured according to standard protocols and techniques. BMI was calculated as follows: BMI= weight (Kg)/ height (M2).The cut-off points of BMI were normal (18.5-24.9kg /m2), overweight (25.0-29.9kg /m2) and obese (BMI≥ 30.0kg /m2). IR was indexed by the homeostasis model assessment (HOMA) formula: [fasting insulin (μU/mL)×fasting glucose (mmol/L)]/22.5 In this study, the value was 3.7, representing the diagnostic value of IR for the entire study population, rather than the general sample.
Evaluation Criterion
Telomere
Telomere length analysis in this trial was performed at the University of California, San Francisco using polymerase chain reaction to measure telomere length relative to standard reference DNA(T/S) ratios. Each sample was tested three times over a 3-day period, on repeated 6 Wells, to identify and rule out any potential outliers (<2% of the sample).About all the details, please visit http://cdc.gov/nchs/nhanes lab section. The coefficient of variation between batches was 6.5%.The value represents the mean (standard deviation) of the T/S ratio. The Centers for Disease Control (CDC) approved human subjects for this measure through the CDC Institutional Review Board and ensured quality control of the TL measurements prior to establishing a data link to the NHANES database.
Smoking
In this study, we divided smoking into two levels. Smoker: refers to having smoked more than 100 cigarettes in a lifetime or having smoked more than one cigarette on average in the last 30 days. Non-smokers: refer to those who have smoked no more than 100 cigarettes in their lifetime or no more than one cigarette on average in the past 30 days.
hypertension
Hypertension was defined as resting systolic and/or diastolic blood pressure ≥140/90 mmHg (20). Another relatively strict standard is based on the 2017 American College of Cardiology/American Heart Association Blood Pressure Guidelines (21).Blood pressure <130/80 mmHg is recommended as normal. Hypertension was defined as having three mean BP of >130/80 or taking hypertensive medication.
Education
In this study, we divided the educational level of the participants into two levels, one was the participants who had received higher education, or at least tertiary education. Second, those who have not received higher education, those who have not received college education or above.
Income
In this study, we divided the family income into two levels, one is the family income of less than $100,000 a year low-income families. Second, high-income families with a household income of $100,000 or more a year.
Covariable Selection
The potential confounders of possible associations between Telomere length and risk of insulin resistance outcomes were defined a priori based on the literature.
Our covariates were selected apriori based on our prior work and studies from others examining risk factors for insulin resistance.
Statistical Approach
In order to make the sample more representative, we use NHANES database with complex, multi-stage probability sampling design. The study looked at a nationally representative sample; Each year, 5,000 people are selected from a sampling framework of 15 different locations across all counties in the United States. The prevalence of IR is a weighted percentage of IR in the complex sample, equal to the number of IR patients divided by the total number of IR patients. The statistical analysis was performed using the R 3.4.3 version. Continuous variables are expressed as detailed sample descriptions, with averages and 95% confidence intervals. Classification variables are expressed as counts and weighted percentages, using complex sample frequencies. Continuous variables were compared between groups using student t test or Mann-Whitney U test based on distribution normality, and classification variables were compared using Fisher's exact test.
We established three logistic regression models to test the risk of telomere length and insulin resistance, and analyzed the models according to covariates such as age, gender, race and BMI. After adjustment, multiple logistic regression was used to test the relationship between the risk of insulin resistance and telomere length in each subgroup.