Relationship between underweight, bone mineral density and skeletal muscle index in premenopausal Korean women

Being underweight, academic performance and cognitive control in undergraduate women

The prevalence of underweight among young women is a serious international health issue. However, the evidence on how being underweight negatively affects brain health and cognition is still unclear. This study investigated the association between underweight status, academic performance, and neurocognitive control in young Japanese women using a cross-sectional design. We analyzed the academic performance of female undergraduates, comparing underweight and healthy-weight groups (n = 43; age 18-23 years, M = 21.1, SD = 1.3) based on their grade point average (GPA). We also analyzed their error-related negativity (ERN), an electrophysiological measure that potentially reflects academic performance, during an arrowhead version of the flanker task to assess cognitive control of action monitoring. Participants with a low body mass index were found to have lower GPAs. Furthermore, the underweight students exhibited smaller ERN amplitudes, which indicates decreased cognitive control in action monitoring. These findings suggest that a healthy weight status is essential for effective cognitive functioning and academic success in young adult women, among whom being underweight is a serious health problem.

Skeletal muscle index together with body mass index is associated with secondary osteoporosis in patients with rheumatoid arthritis

OBJECTIVE

The objective of this study was to explore the associations of body mass index (BMI), fat mass index (FMI), skeletal mass index (SMI) and secondary osteoporosis (OP) in patients with rheumatoid arthritis (RA).

METHODS

The bone mineral density (BMD) at sites of the femur neck (Neck), total hip (Hip) and lumbar vertebrae 1-4 (L1-4) was measured by dual-energy X-ray absorptiometry. The skeletal muscle index, body fat percentage and mineral content were measured by biological electrical impedance for calculating BMI, FMI and SMI.

RESULTS

A total of 433 patient with RA and 158 healthy controls were enrolled. The BMDs at each site of the RA patients were lower compared with those of the healthy controls (p < 0.0001), and the prevalence of OP (36.1%, 160/443) and sarcopenia (65.2%, 288/443) in the RA patients were higher than those in the controls (12.7%, 20/158, p < 0.0001; 9.0%, 14/156, p < 0.0001). Significant differences in the BMD, FMI, SMI, mineral content, body fat percentage and skeletal muscle mass were found among the RA patients in the different BMI groups (p < 0.05). In RA patients with BMI < 18.5 kg/m2, the prevalence of OP in the RA patients with sarcopenia was similar to that in those without sarcopenia (44.4% vs. 66. 7%, χ2 = 0. 574, p = 0.449). In the RA patients with a normal BMI or who were overweight or obese, prevalence of OP in the RA patients with sarcopenia was significantly higher than that in the RA patients without sarcopenia (42.8% vs. 21.7%, χ2 = 10.951, p = 0.001; 61.1% vs. 13.0%, χ2 = 26.270, p < 0.0001). In the RA patients without sarcopenia, the prevalence of OP in the RA patients in the different BMI groups was different (p = 0.039). In the RA patients with sarcopenia, there was no significant difference in the prevalence of OP among the RA patients in the different BMI groups (p = 0. 128). The linear correlation analysis showed that the SMI in RA patients was positively correlated with the BMD of each site measured and BMI and FMI (p < 0.0001). However, there was a negative linear correlation between SMI and disease duration (p = 0.048). The logistic regression analysis found that SMI (OR = 0.569, p = 0.002, 95% CI 0.399-0.810), BMI (OR = 0.884, p = 0.01, 95% CI 0.805-0.971) and gender (1 = female, 2 = male) (OR = 0.097, p < 0.0001, 95% CI 0.040-0.236) were protective factors for OP in RA, while age (OR = 1.098, p < 0.0001, 95% CI 1.071-1.125) was the risk factor.

CONCLUSION

BMI and SMI are associated with the occurrence of OP in RA patients, and both SMI and BMI are important protective factors for OP secondary to RA.

Bone mineral density and body mass composition measurements in premenopausal anorexic patients: the impact of lean body mass

INTRODUCTION

Evaluating bone density and body composition by dual-energy x-ray absorptiometry (DXA) and analyzing their relationships among young anorexic women in comparison with normal-lean matched controls.

MATERIALS AND METHODS

In this observational cohort study, 98 normal-underweight young females were enrolled (aged more than 16 and less than 24 years). The study group included 68 anorexic patients and 30 healthy age-matched controls. The patients underwent a DXA examination to evaluate bone mineral density and body composition. Several indexes of body composition were used: the FMI (Fat Mass Index), the TLMI (Total Lean Mass Index) and the SMI (Skeletal Muscle mass Index) the last one as a marker of sarcopenia.

RESULTS

According to the ISCD (International Society for Clinical Densitometry) criteria, a significantly higher percentage of anorexic patients were found to be below the expected range for age as compared to controls (P < 0.01). According to WHO criteria, 20% of the anorexic patients presented an osteoporotic T-score index at the lumbar level and 18% presented an osteoporotic T-score at the femoral level. As regards the lean body characteristics, the SMI and TLMI were significantly lower in the anorexic population (P < 0.01 and P < 0.001, respectively) and 24% of the anorexic patients presented SMI values that are indicative of pre-sarcopenia. In addition, only the SMI significantly correlated with both the lumbar and the femoral BMD values.

CONCLUSION

Anorexic patients have a very high risk of osteoporosis and fractures. Bone density is influenced by fat body mass and also significantly by lean body mass. Special consideration should be given to the sarcopenic condition since it is a worsening factor of bone health.

Risk of fracture according to temporal changes of low body weight changes in adults over 40 years: a nationwide population-based cohort study

BACKGROUND

Low body weight is associated with an increased risk of fractures. However, the effect of temporal changes in the low body weight status on the risk of fracture remains unknown. This study aimed to evaluate the relationships between temporal changes in low body weight status and the risk of fractures in adults over the age of 40 years.

METHODS

This study included data on adults over 40 years old who underwent two biannual consecutive general health examinations between January 1, 2007 and December 31, 2009 extracted from the National Health Insurance Database, a large nationwide population database. Fracture cases in this cohort were monitored from the time of the last health examination to the end of the designated follow-up period (from January 1, 2010 to December 31, 2018) or the participant's death. Fractures were defined as any fracture resulting in hospitalization or outpatient treatment claim after the date of general health screening. The study population was then separated into four groups based on the temporal changes in low body weight status as follows: low body weight to low body weight (L-to-L), low body weight to non-low body weight (L-to-N), non-low body weight to low body weight (N-to-L), and non-low body weight to non-low body weight (N-to-N). The hazard ratios (HRs) for new fractures, depending on weight changes over time, were calculated using Cox proportional hazard analysis.

RESULTS

Adults in the L-to-L, N-to-L, and L-to-N groups had a substantially increased risk of fractures after multivariate adjustment (HR, 1.165; 95% confidence interval [CI], 1.113-1.218; HR, 1.193; 95% CI, 1.131-1.259; and HR, 1.114; 95% CI, 1.050-1.183, respectively). Although the adjusted HR was greater in participants who changed into having a low body weight, followed by those with consistently low body weight, those with low body weight remained to have an elevated risk of fracture independent of weight fluctuation. Elderly men (aged over 65 years), high blood pressure, and chronic kidney disease were significantly associated with an increase in fractures (p < 0.05).

CONCLUSION

Individuals aged over 40 years with low body weight, even after regaining normal weight, had an increased risk of fracture. Moreover, having a low body weight after having a normal body weight increased the risk of fractures the most, followed by those with consistently low body weight.

Underweight and risk of fractures in adults over 40 years using the nationwide claims database

We aimed to investigate how underweight affects the incidence of fractures, as well as the influence of cumulative, longitudinal periods of low body mass index (BMI) and changes in body weight on fracture development. Data on adults aged 40-year and over who had three health screenings between January 1, 2007, and December 31, 2009 were used to determine the incidence of new fractures. The hazard ratios (HRs) for new fractures depending on BMI, total cumulative number of underweight, and weight change over time were calculated using Cox proportional hazard analysis. In this study, 15,955 (2.8%) of the 561,779 adults were diagnosed with fractures more than once over three health examinations. The fully adjusted HR for fractures in underweight individuals was 1.173 (95% Confidence interval [CI] 1.093-1.259). Underweight individuals diagnosed only once, twice, or three times had an adjusted HR of 1.227 (95%CI 1.130-1.332), 1.174 (95%CI 1.045-1.319), and 1.255 (95%CI 1.143-1.379), respectively. Although the adjusted HR was higher in adults who consistently had underweight (HR; 1.250 [95%CI 1.146-1.363]), those with underweight had an increased risk of fractures regardless of weight change (HR; 1.171 [95%CI 1.045-1.312], and 1.203[95%CI 1.075-1.346]). Underweight is a risk factor for fractures in adults over the age of 40 years, even if they returned to normal weight.

Alternative skeletal muscle index for sarcopenia diagnosis in elderly patients with type 2 diabetes mellitus: A pilot study

PURPOSE

To determine an alternative skeletal muscle index (a-SMI), easy diagnosis of sarcopenia in elderly patients with type 2 diabetes mellitus (T2DM).

PATIENTS AND METHODS

This cross-sectional study included 223 inpatients with T2DM (100 males, age range 60-89; 123 females, age range 60-87). Screening for grip strength and gait speed, measuring SMI by dual-energy X-ray absorptiometry (d-SMI) for sarcopenia diagnosis, according to the Asian Working Group for Sarcopenia (AWGS) 2019 consensus. The a-SMI was established by binary logistic regression analysis with positive screening population. To assess the conformance of the new diagnostic approach with the AWGS 2019.

RESULTS

Sarcopenia was present in 36.3% of the study population. 59 had normal d-SMI and 81 had low d-SMI in screening patients with probable sarcopenia. In univariate analyses for all positive screening population, body mass index (BMI), 25-hydroxyvitamin D (25 - (OH) VitD), high density lipoprotein cholesterol (HDL-C), hypertension (HTN), and gender were correlates of d-SMI. Binary logistic regression analysis revealed that male (B = 2.463, 95%CI: 3.640 ~ 37.883, p = 0.000), HTN (B = 1.404, 95%CI: 1.599 ~ 10.371, p = 0.003), BMI (B = -0.344, 95%CI: 0.598 ~ 0.839, p = 0.000), 25-(OH) VitD (B = -0.058, 95%CI: 0.907 ~ 0.982, p = 0.004) were independent factors for d-SMI detection. Based on the extracted four correlates, the a-SMI was determined. The area under receiver operating characteristic (ROC) curve was 0.842, sensitivity and specificity for the new diagnostic approach were 84.0% and 84.5%. In a statistical measure of agreement between the AWGS 2019 and the new diagnostic approach, the kappa coefficient was 0.669 (p < 0.001).

CONCLUSION

The a-SMI - based on gender, obesity status, 25-(OH) VitD, and HTN history - can be used in the absence of the d-SMI to supplement the algorithm for sarcopenia diagnosis in elderly patients with T2DM.

Association of Different Obesity Phenotypes with Sarcopenia in Han Chinese Middle-Aged and Elderly with Type 2 Diabetes Individuals

PURPOSE

To investigate the relationship between different obesity phenotypes and sarcopenia in hospitalized Chinese patients with type 2 diabetes mellitus (T2DM).

METHODS

This cross-sectional study included 385 men. Anthropometric measurements including applied the determination method of Dual-energy X-ray absorptiometry (DXA) determination of limb skeletal muscle mass index (ASMI) and blood samples were analyzed. The people were divided into four groups according to body mass index (BMI) (≥24kg/m²) and waist circumference (WC) (female ≥85cm, male ≥90cm). Group A (BMI and WC were normal), Group B (BMI was normal and high WC), Group C (high BMI and WC were normal), and Group D (BMI and WC were abnormal).

RESULTS

The prevalence rates of sarcopenia and abdominal obesity were 32.2% and 74.0%, respectively. The detection rate of lower ASMI decreased gradually from Group A to Group D(74.6% vs 68.3% vs 54.5% vs 51.6%, χ 2 =14.243, P=0.003). Logistic analysis showed that the risk of lower ASMI were decreased by 62.4% (95% CI: 0.149-0.950, P = 0.039) in Group C and 68.8% (95% CI: 0.165-0.593, P = 0.000) in Group D compared with Group A, respectively. The risk of lower ASMI were increased 4.153-fold (95% CI: 2.623-6.576, P = 0.000) in male. Male (OR = 4.065, 95% CI: 2.246-7.356, P = 0.000) and WC (OR = 1.053, 95% CI: 1.004-1.104, P = 0.033) were risk factors for lower ASMI, but the risk of lower ASMI was decreased by 32% (95% CI: 0.5744-0.804, P = 0.000) by elevated BMI in the overweight and obese group (Group C and Group D).

CONCLUSION

The prevalence of sarcopenia and abdominal obesity was elevated in han Chinese middle-aged and elderly patients with T2DM. Being overweight or obesity as defined by BMI protect against sarcopenia, while abdominal obesity increases the risk of sarcopenia.

Severity of underweight and risk of fracture: a Korean nationwide population-based cohort study

Underweight is an important modifiable risk factor for fractures. However, there have been few large cohort studies regarding the relationship between underweight and fracture in the general population. We investigated the risk of fracture development according to underweight severity in a large population cohort. This nationwide cohort study included 2,896,320 people aged ≥ 40 years who underwent national health checkups in 2009 and were followed up to identify the incidence of fracture until December 31, 2018. After applying the exclusion criteria that included overweight and obese individuals, the study population was divided according to body mass index (BMI) into normal weight (18.5 ≤ BMI < 23.0), mild underweight (17.5 ≤ BMI < 18.5), moderate underweight (16.5 ≤ BMI < 17.5), and severe underweight (BMI < 16.5) groups. Cox proportional hazards regression analyses were performed to calculate the hazard ratios for risk of fracture according to underweight severity. Severely underweight participants had a 28% increased fracture risk (adjusted hazard ratio [HR] 1.28, 95% confidence interval [CI] 1.20-1.37) compared with those of normal weight. In addition, fracture risk was increased by 14% in individuals with moderate underweight (adjusted HR 1.14, 95% CI 1.08-1.19) and 9% in those with mild underweight (adjusted HR 1.09, 95% CI 1.06-1.13). The severity of underweight was significantly associated with risk of fracture.

Nutritional status and associated factors of older persons in sub-Saharan Africa: a scoping review

BACKGROUND

The older person population is rapidly increasing globally, including sub-Saharan Africa (SSA). Concurrently, malnutrition is also increasing among older persons in SSA, with a dearth of empirical evidence on nutritional status and associated factors among the older persons in the region to inform effective interventions to promote healthy ageing.

AIM/OBJECTIVE

This review assessed the nutritional status and associated factors among older persons in SSA.

METHOD

PubMed, Google Scholar, and Cochrane Library electronic databases were searched for published articles from 2010 to 2021 using keywords and Boolean logic. Also, we carried out a free web-based search to retrieve other relevant evidence that assesses the older persons' nutritional status. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart was used to appraise the research articles that responded to the study's research questions.

FINDINGS

Twenty studies met the inclusion criteria, from which data were extracted as findings. The malnutrition prevalence was between 6 to 54% among older persons in SSA. We found that the prevalence of malnutrition vary and could be as high as 28.4% in a low socio-economic status area. Of these studies, twelve (12) provided data on undernutrition with prevalence ranging from 2.9 to 41%;10 provided data on overweight (8.1-54.1%) and 5 on obesity (2.7-44.7%). Seventeen of the studies evaluated factors associated with malnutrition; 4 studies revealed the association between socioeconomic status and malnutrition, 7 studies reported a significant association between dietary habits and malnutrition. Four studies showed an association between educational status and malnutrition. Disease conditions associated with malnutrition were reported in four of the studies.

CONCLUSION

This review shows that malnutrition is a problem among older persons in SSA coupled with many risk factors which should be given critical attention. We recommend nutrition education for older persons as well as the development of nutrition interventions for this vulnerable group.

Body fat prediction through feature extraction based on anthropometric and laboratory measurements

Obesity, associated with having excess body fat, is a critical public health problem that can cause serious diseases. Although a range of techniques for body fat estimation have been developed to assess obesity, these typically involve high-cost tests requiring special equipment. Thus, the accurate prediction of body fat percentage based on easily accessed body measurements is important for assessing obesity and its related diseases. By considering the characteristics of different features (e.g. body measurements), this study investigates the effectiveness of feature extraction for body fat prediction. It evaluates the performance of three feature extraction approaches by comparing four well-known prediction models. Experimental results based on two real-world body fat datasets show that the prediction models perform better on incorporating feature extraction for body fat prediction, in terms of the mean absolute error, standard deviation, root mean square error and robustness. These results confirm that feature extraction is an effective pre-processing step for predicting body fat. In addition, statistical analysis confirms that feature extraction significantly improves the performance of prediction methods. Moreover, the increase in the number of extracted features results in further, albeit slight, improvements to the prediction models. The findings of this study provide a baseline for future research in related areas.

Body mass index and self‐rated oral health in Korean adults in 2017

OBJECTIVE

To investigate the association between obesity and self-rated oral health (SROH). This study examined the cross-sectional associations between body mass index (BMI) and SROH in Korean adults.

MATERIALS AND METHODS

This study used data from 217 304 adults (100 110 men and 117 194 women aged > 19 years) from the 2017 Korean Community Health Survey. Participants were categorised into six ordinal groups based on BMI: underweight (<18.5 kg/m² ), normal weight (18.5-22.9 kg/m² ), overweight (23.0-24.9 kg/m² ), obese-I (25.0-27.4 kg/m² ), obese-II (27.5-29.9 kg/m² ) or obese-III (≥30.0 kg/m² ). SROH was assessed using responses to the question, "How do you rate your oral health, including your teeth and gums?" rated on a 5-point scale. SROH was categorised as "good" (reported as "fair," "good" or "very good") or "poor" or "very poor." Age- and sex-stratified associations between BMI categories and poor SROH were assessed using ordinal logistic regression analysis with sampling weights.

RESULTS

The age-adjusted odds ratio (OR) for poor SROH according to BMI levels was lowest in the overweight group in both men and women. In men, the OR for poor SROH was 2.03 (99% confidence interval [CI], 1.72-2.39) in the underweight group, 1.17 (99% CI, 1.17-1.25) in the normal group, 1.05 (99% CI, 0.98-1.13) in the obese-I group, 1.08 (99% CI, 0.98-1.18) in the obese-II group and 1.36 (99% CI, 1.20-1.55) in the obese-III group. In women, the OR was 1.18 (99% CI, 1.07-1.31) in the underweight group, 1.01 (99% CI, 0.95-1.07) in the normal group, 1.07(99% CI, 0.99-1.16) in the obese-I group, 1.16 (99% CI, 1.04-1.30) in the obese-II group and 1.39 (99% CI, 1.20-1.62) in the obese-III group. From the restricted cubic spline models in both sexes, BMI showed a J-shaped association with poor and very poor SROH in men and women. In a stratified analysis by age group and sex, men and older women in the underweight group had poorer SROH than those in overweight group.

CONCLUSION

In a nationally representative sample of Korean adults, there was a J-shaped association between BMI and poor SROH, with the highest risk in the underweight group amongst men and in the obese-III group amongst women. Furthermore, in men and women over 65 years of age, underweight and obesity were associated with poorer SROH.

Biochemical, hematologic, and skeletal features associated with underweight, overweight, and eating disorders in young Korean women: A population-based study

BACKGROUND

Extreme weight conditions in young women are associated with adverse health outcomes. Closely linked with extreme weight status, eating disorders (EDs) are associated with several medical complications and high mortality rates.

OBJECTIVE

The study aimed to investigate the biochemical, hematologic, and skeletal features of young Korean women with underweight (UW) and overweight/obesity (OW) conditions, and patients with anorexia nervosa (AN) and bulimia nervosa (BN) compared to women with normal-weight (NW).

METHOD

A total of 808 women (mean age 22.3 ± 3.4 years) were recruited for the study, including 144 with UW status [body mass index (BMI) < 18.5 kg/m²], 364 with NW, 137 with OW or obesity (27 with obesity; BMI ≥ 25 kg/m²), 63 patients with anorexia nervosa (AN), and 100 with bulimia nervosa (BN). We measured blood pressure and performed biochemical, hematologic and bone mineral density (BMD) evaluations at the lumbar and femoral neck.

RESULTS

Blood pressure and triiodothyronine levels were found to be lower in both ED groups and higher in the OW group, but no difference in the UW group, compared to the NW group. The aminotransferases and total cholesterol levels were higher in the ED and OW groups, compared to the NW group. Blood cell counts were decreased in the AN group, while increased in the OW group, compared to the NW group. Blood urea nitrogen was elevated in both ED groups. The UW and AN groups had lower BMD, whereas the OW group had higher BMD, compared to the NW group.

CONCLUSION

Our findings suggested that both ED groups were associated with decreases in the resting energy expenditure. OW status was associated with a risk of metabolic syndrome, and UW status with lower BMD in young women. Overall, the medical parameters in Korean patients with ED were similar to the patterns reported in Western samples in previous studies, with few exceptions such as potassium level in BN.

The association of extreme body weight with bone mineral density in Saudi children

Objective:

The objective to investigate the effect of extreme body weight; obesity and undernutrition, on bone mineral density (BMD).

Methodology:

This study is a descriptive cross-sectional study carried between January and June of 2019, and included 224 children and adolescents without any comorbidities or chronic disease. Important data collected included anthropometrics, past medical and surgical history, history of medication intake, level of physical activity and pubertal assessment. Data entry and analysis were conducted using Statistical Package for Social Sciences version 24.

Results:

Gender distribution showed 48.2% were male and 51.8% were female. The mean age was 9.98 ± 3.5 years. Mean weight was 34.89 ± 18.2 kg. Mean BMD z-score was − 1.64 ± 1.4. Weight was considered to significantly correlate with BMD stature at a P = 0.014. Subjects who were underweight showed a lower mean BMD z-score of <−2 than those who were overweight/obese (mean BMD z-score = −1.60).

Conclusion:

Both extremes of weight are considered a significant risk factor for the development of low BMD in children. We recommend the early recognition of weight aberrations and consequent aggressive intervention with strict lifestyle modifications to promote the development of maximum peak bone mass.

Nutrition, Physical Activity, and Dietary Supplementation to Prevent Bone Mineral Density Loss: A Food Pyramid

Bone is a nutritionally modulated tissue. Given this background, aim of this review is to evaluate the latest data regarding ideal dietary approach in order to reduce bone mineral density loss and to construct a food pyramid that allows osteopenia/osteoporosis patients to easily figure out what to eat. The pyramid shows that carbohydrates should be consumed every day (3 portions of whole grains), together with fruits and vegetables (5 portions; orange-colored fruits and vegetables and green leafy vegetables are to be preferred), light yogurt (125 mL), skim milk (200 mL,) extra virgin olive oil (almost 20 mg/day), and calcium water (almost 1 l/day); weekly portions should include fish (4 portions), white meat (3 portions), legumes (2 portions), eggs (2 portions), cheeses (2 portions), and red or processed meats (once/week). At the top of the pyramid, there are two pennants: one green means that osteopenia/osteoporosis subjects need some personalized supplementation (if daily requirements cannot be satisfied through diet, calcium, vitamin D, boron, omega 3, and isoflavones supplementation could be an effective strategy with a great benefit/cost ratio), and one red means that there are some foods that are banned (salt, sugar, inorganic phosphate additives). Finally, three to four times per week of 30-40 min of aerobic and resistance exercises must be performed.

Potential mechanisms linking psychological stress to bone health

Chronic psychological stress affects many body systems, including the skeleton, through various mechanisms. This review aims to provide an overview of the factors mediating the relationship between psychological stress and bone health. These factors can be divided into physiological and behavioural changes induced by psychological stress. The physiological factors involve endocrinological changes, such as increased glucocorticoids, prolactin, leptin and parathyroid hormone levels and reduced gonadal hormones. Low-grade inflammation and hyperactivation of the sympathetic nervous system during psychological stress are also physiological changes detrimental to bone health. The behavioural changes during mental stress, such as altered dietary pattern, cigarette smoking, alcoholism and physical inactivity, also threaten the skeletal system. Psychological stress may be partly responsible for epigenetic regulation of skeletal development. It may also mediate the relationship between socioeconomic status and bone health. However, more direct evidence is required to prove these hypotheses. In conclusion, chronic psychological stress should be recognised as a risk factor of osteoporosis and stress-coping methods should be incorporated as part of the comprehensive osteoporosis-preventing strategy.

High Visceral Fat Area Attenuated the Negative Association between High Body Mass Index and Sarcopenia in Community-Dwelling Older Chinese People

The association between obesity and sarcopenia remains controversial. The present study was conducted to explore the associations among body mass index (BMI), visceral fat area (VFA), and sarcopenia in older people and analyze their potential mechanisms. This cross-sectional study included 861 community-dwelling older Chinese people from three regions of China. BMI, VFA, muscle mass, muscle strength, physical performance, body composition, and metabolic markers were measured. Muscle mass and muscle strength were positively correlated with BMI, but were negatively correlated with VFA. Simple overweight/obesity was negatively associated with sarcopenia (OR = 0.07, 95% CI = 0.03~0.18), and the OR value was lower than combined obesity (OR = 0.16, 95% CI = 0.09~0.28). Fat free mass and total body protein were positively associated with high BMI but negatively associated with high VFA. Furthermore, high VFA was adversely associated with some metabolic risk factors of sarcopenia. Combination of BMI and VFA increased diagnostic efficiency of low muscle mass and sarcopenia. In conclusion, high BMI was negatively associated with sarcopenia, while high VFA attenuated the negative association between high BMI and sarcopenia. The opposite association may partially be attributed to their different associations with body composition and metabolic risk factors of sarcopenia. Therefore, bedsides BMI, VFA and its interaction with BMI should be considered in sarcopenia prevention.

Depression, anxiety and health status across different BMI classes: A representative study in Germany

BACKGROUND

Changes in body mass index (BMI) over the course of one's lifetime are related to the development of mental disorders. In the current study we compared symptoms of depression, generalized anxiety as well as general health status in the four BMI-classes: underweight, normal weight, overweight and obesity. Furthermore, mediator role of general health status on the relationship between BMI and depression and generalized anxiety was analyzed.

METHODS

A representative sample (random-route sampling) of the German population (N = 2350) was investigated in a cross-sectional survey by measuring the three questionnaires PHQ-9, GAD-7 and EQ-5D-5L.

RESULTS

The results showed significant differences between the four BMI-classes in all three questionnaires. Individuals with obesity demonstrated higher values in depression, anxiety and general health compared to the three other BMI-classes. However, there was no U-shaped association between BMI and depression, anxiety and health-related quality of life. Regarding to the mediation analysis, general health status fully mediated the association between BMI, depressive symptoms as well as generalized anxiety symptoms.

LIMITATIONS

The assessment of the three factors depression, anxiety and general health status were measured by questionnaires, but no clinical diagnoses can be provided.

CONCLUSIONS

Evidence supports that individuals with obesity have an increased risk for depression and anxiety as well as lower general health. Further research on potential intervention and strategies in public health policies is needed to be able to target the developing of mental disorders in individuals with obesity. Taking their general health status into account is also of great importance.

A Review of Selected Studies on the Factors Associated with the Nutrition Status of Children Under the Age of Five Years in South Africa

Malnutrition is a considerable contributor to child mortality and morbidity. Child malnutrition further affects the country's economic development. Child malnutrition in South Africa is persistent, continuing to be an alarming burden. The nutritional status of kids under the age of five years is a critical indicator of the country's economic condition and health status. An understanding of the influencers of the nutritional status of children can act as a catalyst in combatting all forms of malnutrition. The purpose of this paper was to review selected studies concerning the factors that affect the nutritional status of children in South Africa. Studies were selected from electronic databases, which were PubMed, Google Scholar, Science Direct, Sabinet African Journals, and the University of Zululand library catalog. The keywords that were used to search studies and articles from the selected database were: risk factors, child nutritional status, children under the age of five years, South Africa, malnutrition, underweight, stunted, wasting, and over-nutrition. Studies and surveys published from 2010-2019 that reported on the factors influencing the nutritional status of children under the age of five years were included in this review. Twenty-seven articles met the inclusion criteria of the study. The 27 articles were made up of 21 cross-sectional articles and six longitudinal articles. The finding from this review highlights that there is a lack of studies conducted in urban areas. The results show that the nutritional status of children is affected by several factors. These include household food insecurity, low household income, illiterate caregivers, unemployment, inadequate dietary intake, low birth weight, consumption of monotonous diets, poor caregiver's nutritional knowledge, poor access to water and sanitation, poor weaning practices, age of the caregiver, and demographic characteristics of a child (age and gender). It is critical to have an understanding of the factors that affect the nutritional status of children. Such knowledge can significantly contribute to formulating policies that can enhance nutrition security and the country's economy. Moreover, insights into strategic interventions to eradicate all forms of malnutrition can be made.

The relationships between bone variables and physical fitness across the BMI spectrum in young adult women

In this cross-sectional study we aimed to evaluate the relationship between physical fitness and bone variables across the body mass index (BMI) spectrum in women aged 20-35 years. The study included 13 underweight women (BMI < 18.5 kg/m²), 24 normal weight women (BMI 18.5-24.9 kg/m²), and 20 overweight/obese women (BMI ≥ 25 kg/m²) aged between 20 and 35 years. Bone mineral density (BMD) and content (BMC) at the whole body, lumbar spine, and femoral neck, lumbar spine trabecular bone score, femoral neck geometry were assessed using dual-energy X-ray absorptiometry. Cardiorespiratory fitness and lower limb muscle power were estimated using the 20-m shuttle run test and the Sargent jump test, respectively. The associations between bone variables and physical fitness were different according to BMI categories. Correlations between physical fitness and bone parameters are particularly significant in normal BMI and less significant in low and high BMI. Multivariate ANCOVA regression models demonstrated that absolute VO_2max (L/min) is a strong determinant of all the bone parameters regardless of BMI. Implementing strategies for increasing VO_2max (L/min) by increasing lean mass and promoting resistance and/or high-intensity interval training could be effective to optimize bone health in underweight and overweight young adult women.

Analysis of bone mass and its relationship with body composition in school-aged children and adolescents based on stage of puberty and site specificity: A retrospective case-control study

The aim of this study was to better understand the relationship of bone mass with body composition based on different stages of puberty and to illuminate the contribution of site-specific fat mass and lean mass (FM and LM) compared with bone mass in school-aged children and adolescents in Chongqing, China.A total of 1179 healthy subjects of both sexes were recruited. Bone mineral content (BMC), bone mineral density (BMD), bone area, and both FM and LM were measured by dual-energy X-ray absorptiometry (DXA). The fat mass and lean mass indexes (FMI and LMI, respectively) were calculated as the FM (kg) and LM (kg) divided by the height in meters squared, respectively.Most of the bone mass indicators were significantly higher for postpubertal boys than for girls at the same stage (P < .001). The proportion of subjects with normal bone mass increased, while the proportion of subjects with osteopenia and osteoporosis decreased with increased body weight regardless of gender and puberty stage (P < .01). FM and LM were significantly positively related to bone mass regardless of gender and puberty stage (P < .0001). FMI and LMI were significantly positively related to bone mass in most conditions (P < .05 and P < .0001, respectively). Four components of the FM and LM were linearly and significantly associated with BMD and BMC for TB and TBHL. Among them, the head fat mass and head lean mass showed the greatest statistical contribution.In the process of assessing bone status, we recommend measuring fat and lean masses, including the fat and lean masses of the head.

Associations between Body Mass Index and Subjective Health Outcomes among Older Adults: Findings from the Yilan Study, Taiwan

Previous findings on the associations between body mass index (BMI) and subjective health outcomes among older adults are inconsistent. The aims of this study were to explore the associations of BMI with health-related quality of life (HRQoL), self-rated health (SRH) and happiness among older adults. This study was part of the Yilan study, which was a community-based survey conducted in the Yilan city in Taiwan. A total of 3722 older adults were randomly recruited during 2012–2016. HRQoL was measured using the Short Form-12 Health Survey physical component summary (PCS) and mental component summary (MCS) scores and SRH and happiness were also evaluated. By hierarchical regression, after adjusting for covariates, compared with normal-weight participants, overweight did not have significantly different PCS scores (B = 0.20, 95% confidence interval [CI]: −0.45 to 0.85, p = 0.546) but obese had significantly lower PCS scores (B = −0.97, 95% CI: −1.68 to −0.26, p < 0.0001); overweight and obese participants had significantly better MCS scores (B = 1.00, 95% CI: 0.40 to 1.61, p = 0.001 and B = 1.22, 95% CI: 0.60 to 1.88, p < 0.0001, respectively); overweight participants had significantly higher SRH scores (B = 1.08, 95% CI: 0.16 to 2.00, p = 0.022) but underweight had significantly lower SRH scores (B = −2.88, 95% CI: −4.81 to −0.95, p = 0.003); overweight and obese participants had better happiness scores (B = 1.55, 95% CI: 0.45 to 2.66, p = 0.006 and B = 1.68, 95% CI: 0.49 to 2.88, p = 0.006, respectively). In conclusion, compared with normal-weight individuals, overweight individuals had better mental HRQoL, SRH and happiness but underweight older people reported poorer SRH and obese reported poorer physical HRQOL but better mental HRQoL and self-rated happiness.

Accuracy of self-reported heights and weights in a predominately low-income, diverse population living in the USA

OBJECTIVES

This study explored the accuracy of self-reported heights and weights and factors associated with self-reported bias in a diverse American sample.

METHODS

Demographic, self-reported, and measured height and weight data from different studies with the same PI were compiled into one SPSS file and analyzed with paired t-tests to detect differences between self-reported and actual values. Kruskal-Wallis tests followed by pairwise t-tests detected differences among age, ethnicity, sex, income, and education. Stepwise regression analyses were done using anthropometric differences as the dependent variable and age category, sex, and ethnicity as independent variables to explore which variable was most predictive of anthropometric differences.

RESULTS

Individuals over-reported height and under-reported weight leading to an under-calculated BMI from self-reported height and weight by 0.6-1 kg/m² . These under-calculations of BMI led to misclassifications of obesity by 3, 6, 8, and 4% for African American, Euro-American, Native American women, and total women, and by 5, 6, 8, and 8% by African American, Euro-American, Native American men, and total men. Older individuals and males over-reported height more than younger individuals and females. African American females over-reported height to a lesser extent than other ethnicities. Asian males over-reported height to a lesser extent than other ethnicities.

CONCLUSIONS

Self-reported heights and weights lead to invalid results. Most individuals over-report height and under-report weight, resulting in an inaccurate underweight and obesity prevalence. Being misclassified into the incorrect BMI category could result in inappropriate healthcare treatment. Age, ethnicity, and sex appear to influence the misreporting of height and weight.