Performance of Body Mass Index in Identifying Obesity Defined by Body Fat Percentage and Hypertension Among Malaysian Population: A Retrospective Study

Figures & data

Table 1 The Characteristics of the Study Population

Indicator	N (%)
Gender
Male	45 (33.1)
Female	91 (66.9)
Age (years)
< 40	85 (62.5)
> 40	51 (37.5)
Education
Primary	7 (5.1)
Secondary	54 (39.7)
University	75 (55.2)
Smoking status
Never	118 (86.8)
Former	5 (3.7)
Current	13 (9.6)
Physical activity
Inactive	67 (49.3)
Active	47 (34.6)
Very active	22 (16.2)
Alcohol intake
Never	117 (86.0)
1–3 unit a week	19 (13.9)
	Mean±SD
Weight (kg)	67.28±16.3
Height (cm)	160.97±7.8
BMI (kg/m^2)	25.9±6.0
Body fat (%)	29.5±10.9
Systolic (mmHg)	120.7±18.6
Diastolic (mmHg)	77.4±11.2

Table 2 Agreement and ROC Analysis Between Standard (27.5 kg/m²) and New BMI (24.8 kg/m²) Cutoffs and BF% in Categorizing Obesity

BMI Cut-off Point (kg/m^2)	Body Fat Percentage		Kappa Value	p-value ^a	Specificity ^b (%)	Sensitivity ^b (%)	Area Under the Curve ^b
	Normal N (%)	Obese N (%)
24.8			0.722	0.058	34.0	80.0	0.778
Normal	57 (93.4)	15 (20.0)
Obese	4 (6.3)	60 (80.0)
27.5			0.532	0.064	98.4	56.0	0.867
Normal	60 (98.4)	29 (42.7)
Obese	1 (1.6)	43 (57.3)

Notes: ^a indicates p-value of kappa analysis; ^b indicates results from receiver-operating characteristic curve.

Figure 1 ROC analysis using body mass index (BMI) at two different cutoff values (standard <27.5 kg/m²; optimal <24.8 kg/m²). The area under the curve is larger for BMI <24.8 kg/m² compared to <27.5 kg/m².

Table 3 The Association Between Hypertension and Obesity Defined Using Standard (27.5 kg/m²) and New Cutoff Values (24.8 kg/m²)

BMI Cut-Off Point (kg/m^2)	Normotensive (n = 100)	Hypertensive (n=36)	χ^2 value ^a	p-value ^a	OR ^b	95% CI ^b
BMI (>24.8)			5.566	0.018*	2.546	1.158–5.600
Normal n (%)	59 (59.0)	13 (36.1)
Obese n (%)	41 (41.0)	23 (63.9)
BMI (>27.5)			0.316	0.574	1.258	0.565–2.804
Normal n (%)	69 (69.0)	23 (63.9)
Obese n (%)	31 (31.0)	13 (36.1)

Notes: *Significant level at p<0.05; ^a indicates results from Chi-square analysis; ^b indicates results from binary logistic regression analysis.

Abbreviations: CI, confidence interval; OR, odds ratio; χ^2, chi-square.