You will be shown the abstract of a medical clinical trial report. Your task is to extract all the findings from this report into a JSON array. Each finding should contain the following five elements:

- Intervention: The medical intervention being tested. This should be a text span copied from the input passage.
- Comparator: The baseline against which the intervention is being evaluated. This should be a text span copied from the input passage. If no comparator is reported, set to `null`.
- Outcome: The medical outcome whose effect is being measured. This should be a text span copied from the input passage.
- Effect: The effect of the intervention on the outcome, relative to the comparator. The effect should be one of the following three values: ("significantly increased", "significantly decreased", "no significant difference").
- Evidence: The evidence for the effect. This should be a text span copied from the input passage.

Please format your output as a JSON array. Each entry in the output should be an array containing the 5 elements listed above, in the following order: [<intervention>, <comparator>, <outcome>, <effect>, <evidence>].

For example, an output with two findings might read:
```
[["aspirin", "placebo", "headache severity", "significantly decreased", "Mean headache severity was significantly decreased in the aspirin group compared to the placebo group (p < 0.05)."], ["aspirin", "placebo", "weight loss", "no significant difference", "We did not observe any difference in weight loss between the group given aspirin relative to the control group"]]
```

There are 2 finding(s) in the abstract below. Please extract them. Output only the JSON array with these 2 findings. Do not include any additional text.

Abstract:
ABSTRACT: The current study aimed to compare the estimates of body fat percentage (%BF) by performing bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA) in a sample of obese or overweight Chinese adults who participated in a weight-loss randomized control trial stratified by gender to determine whether or not BIA is a valid measurement tool. Among 189 adults [73 males, 116 females; age  = 41 to 74 years; mean body mass index (BMI)  = 27.3 kg/m2], assessments of %BF at the baseline and six months from the baseline were conducted by performing BIA and DXA. Bland-Altman analyses and multiple regression analyses were used to assess the relationships between %BFBIA and %BFDXA. Compared with DXA, BIA underestimated %BF [in males: 4.6, –2.4 to 11.7 (mean biases, 95% limit of agreement) at the baseline, 1.4, –7.4 to 10.2 at the endpoint, and 3.2, –4.8 to 11.3 in changes; in females: 5.1, –2.4 to 12.7; 2.2, –6.1 to 10.4; and 3.0, –4.8 to 10.7, respectively]. For males and females, %BFDXA proved to be a significant predictor of the difference between DXA and BIA at the baseline, the endpoint, and in changes when BMI and age were considered (in males: p<0.01 and R
2  = 23.1%, 24.1%, 20.7%, respectively; for females: p<0.001 and R
2  = 40.4%, 48.8%, 25.4%, respectively). The current study suggests that BIA provides a relatively accurate prediction of %BF in individuals with normal weight, overweight, or obesity after the end of weight-loss program, but less accurate prediction of %BF in obese individuals at baseline or weight change during the weight-loss intervention program.

Findings:
[["bioelectrical impedance analysis (BIA)", "dual energy X-ray absorptiometry (DXA)", "body fat percentage (%BF) underestimation at the endpoint in males in obese or overweight Chinese adults", "significantly decreased", "Compared with DXA, BIA underestimated %BF [in males: 4.6, \u20132.4 to 11.7 (mean biases, 95% limit of agreement) at the baseline"], ["bioelectrical impedance analysis (BIA)", "dual energy X-ray absorptiometry (DXA)", "body fat percentage (%BF) underestimation in changes in males in obese or overweight Chinese adults", "significantly decreased", "Compared with DXA, BIA underestimated %BF [in males: 4.6, \u20132.4 to 11.7 (mean biases, 95% limit of agreement) at the baseline"]]