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10.3390/ijerph13070678
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Paul B. Tchounwou
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Yu, C.
Du, J.
Chiou, H.
Feng, C.
Chung, M.
Yang, W.
Chien, L.
Hwang, B.
Sugar-Sweetened Beverage Consumption Is Adversely Associated with Childhood Attention Deficit/Hyperactivity Disorder
Ching-Jung Yu
Jung-Chieh Du
Hsien-Chih Chiou
Chun-Cheng Feng
Ming-Yi Chung
Winnie Yang
Ying-Sheue Chen
Ling-Chu Chien
Betau Hwang
Mei-Lien Chen
1,*
Institute of Environmental and Occupational Health Sciences, School of Medicine, National Yang Ming University, Taipei 11221, Taiwan
Department of Pediatrics, Taipei City Hospital, Zhongxiao Branch, Taipei 11556, Taiwan
Department of Child and Adolescent Psychiatry, Taipei City Hospital, Songde Branch, Taipei 11080, Taiwan
Department of Life Sciences and Institute of Genome Sciences, National Yang Ming University, Taipei 11221, Taiwan
Department of Pediatrics, Taipei City Hospital, Yangming Branch, Taipei 11146, Taiwan
Department of Psychiatry, Taipei Veterans General Hospital, Taipei 11217, Taiwan
School of Public Health, Taipei Medical University, Taipei 11031, Taiwan
Int. J. Environ. Res. Public Health 2016, 13(7), 678; https://doi.org/10.3390/ijerph13070678
Received: 30 April 2016 / Revised: 14 June 2016 / Accepted: 27 June 2016 / Published: 4 July 2016
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Attention deficit/hyperactivity disorder (ADHD) is one of the most common childhood neurobehavioral conditions. Evidence of the negative effects of sugar-sweetened beverages (SSBs) on mental health has not been convincing, although a few studies have found an association between high SSB levels and attention problems in children. This study aimed to test the hypothesis that SSB consumption is associated with ADHD among children. Doctor-diagnosed ADHD cases (n = 173) and non-ADHD controls (n = 159) between age 4 to 15 were recruited. SSB consumption, socio-demographic and lifestyle characteristics of the children, as well as of their mothers' characteristics during pregnancy, were collected using a questionnaire. Blood lead levels and polymorphisms of two commonly verified dopaminergic-related genes (the D4 dopamine receptor gene DRD4 and the dopamine transporter gene DAT1) were also analyzed. There was a dose-response relationship between SSB consumption and ADHD. After covariates were adjusted, children who consumed SSBs at moderate levels and high levels had 1.36 and 3.69 odds, respectively, of having ADHD, compared with those who did not consume SSBs (p for trend < 0.05). Similar results were obtained when females were excluded. Our findings highlighted the adverse correlation between SSB consumption and ADHD and indicated a dose-response effect even after covariates were adjusted.
ADHD; sugar-sweetened beverage; artificial food coloring; preservative; case-control; blood lead level; gene polymorphism; children
In recent years, sugar-sweetened beverages (SSBs) have accounted for 80% of the rise in sugar consumption worldwide. Furthermore, SSBs are the largest single source of added sugar consumption [1,2]. SSBs containing high sugar content may cause insulin secretion, drive reactive hypoglycemia and stimulate an increase in epinephrine, which activates hyperactivity disorder behaviors [3]. Additionally, SSBs often contain other additives, such as artificial food colorings (AFCs) and preservatives that could affect children's behavior [4,5,6,7].
Increasing evidence from animal studies clearly indicates that sugar consumption can cause deficits in cognitive and behavioral functions [8,9,10,11,12]. While many clinical studies on obesity and metabolic disturbances resulting from SSB consumption have been conducted, few studies have examined how SSBs affect development and mental health outcomes [8,13,14,15,16,17,18,19,20,21]. Diet factors, such as sugar consumption, have been linked to an increased risk of attention deficit/hyperactivity disorder (ADHD) [20,22,23]. However, this reported effect is controversial [20,22,23,24,25]. One Norwegian population-based study of 15- to 16-year-old students adopted checklists and questionnaires to assess metal health problems and showed associations between high SSB consumption levels and hyperactivity [20]. A US study of middle school students found that those who consumed SSBs and those who consumed energy drinks had 1.14 and 1.66 odds, respectively, of having ADHD [21]. In a study of disruptive patterns in eating behaviors, Ptacek et al. revealed that male children diagnosed with ADHD exhibited increased sweetened beverage consumption [19]. Their findings suggested that younger children might be susceptible to the adverse effects of SSBs. By contrast, Kim and Chang conducted a Korean study of 107 school-aged children, with only 8.5% categorized as having ADHD, and found no significant association between the consumption of simple sugars, including those in sweets and SSBs, and an increased risk of ADHD [25].
Taiwan has the highest density of chain bubble tea shops and 24-h convenience stores in the world, and both types of stores sell SSBs [26,27]. At the end of 2015, Taiwan had 16,836 bubble tea shops and 10,131 chain convenience stores for a total population of 23.5 million, indicating an average of one store for every 870 people [28]. Researchers have measured the amount of sugar, mainly high-fructose corn syrup (HFCS), added to SSBs and found that it ranged from 22 g to 68 g for a 750 mL serving size [27]. One cross-sectional study evaluated the association between adolescent obesity-related health outcomes and SSB consumption in Taiwan and found that 87.7% of adolescents drank SSBs daily and 25.1% consumed more than 500 mL of SSBs per day [26]. Bubble tea shops have recently arrived in the United Kingdom, Europe, Asia, Australia, Canada and the U.S. [29,30]. Attention should be paid to the intake of these drinks not only because excessive sugar consumption induces metabolic syndrome, which results in excess and imbalanced caloric intake, but also because of its potential association with mental health problems [9,15,20,21,31,32,33], especially among school-aged children.
ADHD is a chronic disease and one of the most common behavioral disorders among children [34,35]. The prevalence of ADHD in children has been reported to range from 7.5% to 9.9% in Taiwan and from 5.9% to 7.1% worldwide [36,37]. ADHD impairs learning and social development; the condition typically develops during the years before school and often persists into adulthood [38,39]. The importance of ADHD prevention and intervention is highlighted by the high prevalence and psychosocial impacts of the disorder. The etiology of ADHD is complex and involves genetic, dietary, and environmental factors that have strong genetic associations, with >70% heritability [40,41,42].
Several studies have assessed the association between SSB consumption and childhood ADHD cross-sectionally [20,21,25]. These studies have measured mental health problems through self-report or interviews with teachers and/or parents. To avoid discordance with the standard nosology of ADHD and prevent misclassification, we ensured that our ADHD cases were diagnosed by doctors based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, revised criteria (DSM-IV-TR). Only few doctor-diagnosed case-control studies have been reported; however, these studies have not controlled potential confounding variables [19]. This is the first case-control study to analyze the association between school-aged children's SSB consumption and ADHD diagnosis by a board-certificated doctor while controlling for covariates. This study hypothesized that children with ADHD drink more SSBs.
2.1. Study Participants and Recruitment
The study protocol was approved by the Taipei Veterans General Hospital and Taipei City Hospital institutional review boards. The project identification codes were 97-01-52A, TCHIRB-1010216 and TCHIRB-1030510 (approved on 4 March 2008, 1 July 2012 and 26 August 2014, respectively). Written informed consent was obtained from the participants' parents or guardians. All participants provided their oral or written assent. This study was conducted in accordance with the revised guidelines of the Declaration of Helsinki. We recruited 4- to 15-year-old subjects from outpatient waiting rooms in both hospitals. In this study, the cases were defined as children with ADHD, as identified by board-certificated pediatricians or psychiatrists after at least a three-visit clinical assessment. Children consecutively admitted for initial and follow-up ADHD treatments were also recruited as cases during the study period. Children with neurological deficits or mental retardation were excluded. The ADHD diagnosis was made in accordance with the DSM-IV-TR criteria [43].
We recruited control subjects by randomly selecting normal 4- to 15-year-old children who visited either of the hospitals for reasons unrelated to ADHD during the same study period, and the same exclusion criteria as those applied to the cases were used. We did not attempt to match cases and controls on gender; however, we matched the two groups on age. Controls were screened for the absence of ADHD symptoms by teachers and parent(s), who assessed children's behaviors in the classroom and at home, respectively, according to the Chinese version of the Swanson, Nolan and Pelham, Fourth Revision (SNAP-IV) questionnaire [44,45]. The rating results were evaluated by pediatricians to confirm the absence of ADHD symptoms. The SNAP-IV Teacher and Parent Rating Scale, which directly adopted DSM-IV symptoms and used the same format, was translated into Chinese and was found to be a reliable and valid tool for screening for ADHD in clinical and research settings in Taiwan [46,47]. The 26-item SNAP-IV questionnaire was based on a four-point (0–3) rating scale and consisted of the DSM-IV ADHD criteria for inattention (items 1–9) and hyperactivity/impulsivity (items 10–18) as well as criteria for oppositional defiant disorder symptoms (items 19–26). If more than six of the nine inattention or hyperactivity/impulsivity items were given a score of a 2 (quite a bit) or 3 (very much) on either the parent's or teacher's form, then the children were defined as at risk of ADHD; otherwise, children were rated as non-ADHD [48]. Children with scores indicating a risk of ADHD were referred to pediatricians or psychiatrists for further confirmation. All cases also received a SNAP-IV score at the initial visit.
We recruited a total of three hundred and thirty-two subjects, one hundred and seventy-three ADHD subjects (n = 173) and one hundred and fifty-nine normal controls (n = 159). The response rates were 63.6% and 58.9% in the case and control groups, respectively. In examining the association between the intake of SSBs and ADHD, we investigated the following covariates: family factors, maternal lifestyle, participants' dietary habits, blood lead levels (BLLs) and gene polymorphisms. In this study, participating subjects' demographic features, dietary habits, mother's lifestyle during pregnancy, and family history of nervous system diseases were collected via questionnaires. For the measurement of BLLs and analysis of gene polymorphisms, subjects provided a blood (or saliva) sample during the clinic visit.
2.2. Dietary Habits, Consumption of SSBs and Intake of Sugar and Calories
We collected information on each child's dietary habits and SSB consumption. A trained interviewer administered a 30-min questionnaire to the mother or other caretaker. The average weekly consumption of meat (including poultry and livestock), milk, eggs, fish, shellfish and other types of seafood was gathered for the previous month. The questionnaire also included questions that estimated the average weekly consumption of vegetable (light-colored vegetables, such as lettuce, cabbage, and bean sprouts, and dark-colored vegetables, such as spinach and broccoli) and fruit servings. The weekly serving was calculated by multiplying the daily servings with frequency of consumption per week over the previous month. One serving of meat, fish, shellfish or other types of seafood was approximately 35 g (for meat and fish, this was approximately the size of one's palm). One cup of milk (approximately 250 mL) and one egg or six quail eggs represented a serving of milk and eggs, respectively. One cup of raw leafy vegetables (approximately the size of the participant's fist) or a half cup of other vegetables represented a serving of vegetables. One serving of fruit was a medium-sized fruit (medium was defined as the size of a baseball) or a half cup of chopped fruit. One serving of SSBs contained 600 mL. Parents or caregivers were asked separate questions about how many servings of milk tea, juice or fruit-flavored drinks, Yakult drinks, and other sugar-sweetened drinks the participants normally consumed. The milk tea referenced in this study is also known as boba milk tea, bubble or pearl tea [49] and is a Taiwanese tea-based drink. It contains a tea base that is mixed/shaken with milk or fruit, and chewy tapioca balls or jellies are often added. Milk tea drinks are part of the larger group of SSB because these beverages are typically HFCS sweetened [50]. Yakult drink is a probiotic dairy product made by fermenting a mixture of milk with a special strain of the bacterium Lactobacillus casei Shirota [51]. This beverage is very popular in Taiwan because it contains probiotics and, thus, is likely considered a healthy drink. However, it also contains high content of sugar (approximately 12 grams for every 100 g of Yakult drink) and is classified as a SSB [52]. When questionnaire items were incomplete, we contacted the mothers or caretakers via telephone to obtain the missing information.
Sugar ingested from SSBs was calculated by multiplying the servings by the sugar content in each type of SSB based on a study of the Ministry of Health and Welfare (MOHW) in Taiwan [52]. In addition, the Taiwan Food and Drug Administration (TFDA) Nutrients Database was used to analyze daily caloric intake [53].
2.3. Measurement of BLLs and Gene Polymorphism Analysis
Peripheral blood was drawn using a syringe or venoclysis needle and then sealed in a heparin-containing vacuum tube and immediately transported at 4 °C to the laboratory. If individuals were not able to supply a blood sample, DNA was extracted from a saliva sample. Saliva was spat into the Saliva DNA Collection and Preservation Kit (Norgen Biotek Corporation, Thorold, ON, Canada) and stored at room temperature until analysis. The sample preparation and analysis of BLLs and gene polymorphism are described elsewhere [42,54]. The BLLs were measured using inductively coupled plasma-mass spectrometry (Thermo Scientific, Waltham, MA, USA). Trace Elements Serum L-2 (Seronorm™, Billingstad, Norway) was used to verify the precision and accuracy of the analytical measurements. The limit of detection (LOD) for lead was 0.001 μg/dL. Regarding gene polymorphism, 10 tagged SNPs (rs7395429, rs3758653, rs11246228, rs752306, rs6347, rs2975292, rs37022, rs40358, rs10040882, and rs464049) of DRD4 and DAT1 were identified and analyzed.
2.4. Covariates
Risk factors potentially associated with ADHD were examined. Predictors were chosen according to their association with ADHD in previous studies. The following variables were considered covariates: gender, body weight, child's age, maternal age at childbirth, gestational age at birth (<37 weeks or ≥37 weeks), parity (primiparous or multiparous) [55,56], birth order (1st, 2nd and 3rd and above), parent's education (high school education and below or college or advanced training), maternal history of still or dead birth (yes or no), maternal smoking during pregnancy (yes or no) [57,58,59], maternal alcohol consumption during pregnancy (yes or no) [59,60], and maternal chronic disease during pregnancy (yes or no). In addition to examining these risk factors, we included family history of nervous system diseases in this study. The nervous system diseases listed in the questionnaire included Parkinson's disease, Alzheimer's disease, ADHD, mental retardation, cerebral palsy, autism, epilepsy, developmental delay, multiple sclerosis and peripheral neuromuscular disease, and the family members considered for this list were the subjects' grandparents, parents and siblings. The variables were obtained from clinical records or questionnaires completed by the mothers or caretakers.
2.5. Statistical and Probabilistic Analysis
SPSS Version 17.0 (SPSS, Chicago, IL, USA) was used for the statistical analysis. We calculated descriptive statistics based on sample sizes and percentages. Next, we assessed the significance of differences between the case and control groups. A 2-sided nonparametric statistical Mann-Whitney U test was used for consecutive data, and a chi-squared test or Fisher's exact test was adopted for categorical data when appropriate [61]. Then, we performed logistic regression analysis with ADHD and the consumption of SSBs. Statistical significance was set at p < 0.05. The covariates related to ADHD at p < 0.05 were controlled in the multivariate analyses. A Kruskal-Wallis test was used to analyze the relationship between ADHD severity and the increased intake of SSBs.
Monte Carlo (MC) simulation, which is a probabilistic analysis, was performed to quantify the theoretical exposure dose range of sugar, AFCs and preservatives. Probability density functions for each parameter were log-normally distributed. Distributions of exposed concentrations and population exposures were estimated by a MC simulation with 5000 replications. Microsoft Excel™ 2010 (Microsoft Inc., Redmond, WA, USA) and Oracle Crystal Ball, Fusion Edition, Release 11.1.2.1.000 software (Oracle Corporation, Redwood City, CA, USA) were used for MC simulation.
3.1. Demographic Characteristics of Participants
Table 1 summarizes the participants' demographic characteristics and other factors by ADHD classification and the corresponding p-values. Among the 332 participants recruited, 173 were diagnosed with ADHD (148 (85.5%) boys and 25 (14.5%) girls) and 159 were normal controls (91 (57.2%) boys and 68 (42.8%) girls). Male ADHD subjects (n = 148) markedly outnumbered female ADHD participants (n = 25). The age distributions of ADHD and normal controls were similar, with a mean age (±SD) of 8.9 ± 2.0 years and 9.2 ± 2.7 years, respectively (p = 0.31). No significant differences in mean age, body weight, child's age, gestational age at birth, parity, birth order, maternal age at birth, maternal history of still or dead birth, maternal smoking during pregnancy, or maternal chronic disease during pregnancy were found between ADHD patients and controls. As the mother's and father's level of education increased, the risk of ADHD decreased (both p < 0.01). Compared with the control subjects, ADHD cases showed significant associations with family history of nervous system diseases and maternal alcohol consumption during pregnancy. As displayed in Table S1, mothers with lower education levels smoked significantly more than those with higher education levels (11.5% vs. 3.1%, respectively; p < 0.01). Additionally, mothers with lower education levels consumed more alcohol than those with higher education levels, but this association was marginally significant (12.2% vs. 6.2%, respectively; p = 0.06).
3.2. Dietary Habits
As shown in Table 2, approximately half of the children in both the control and ADHD groups consumed at least one serving of SSBs each week (56.0% and 48.5%, respectively). ADHD children consumed significantly more servings of SSBs than normal controls (6.96 ± 9.27 vs. 3.10 ± 5.08 servings/week, respectively; p < 0.01). Figure 1 presents the mean and 95% CI of SSB consumption and shows higher levels of SSB consumption among ADHD cases than among controls. ADHD children also ingested significantly more meat and milk (p = 0.04 and p = 0.02, respectively). Control subjects' intake of vegetables and fruits was significantly higher than that of children with ADHD (p < 0.01 and p = 0.02, respectively). No difference was observed in the consumption of eggs, fish and other types of seafood between the two groups.
3.3. Sugar Consumption and Caloric Intake
The levels of sugar intake from SSBs and daily caloric intakes of the ADHD and normal control groups are presented in Table 2. The MOHW in Taiwan reported that the average dietary reference intake (DRI) of children 6- to 12-years-old was 2008 calories, with 2113 calories for boys and 1904 calories for girls [62]. ADHD children's total caloric intake was significantly higher than that of the control subjects (2061.1 ± 689.7 vs. 1801.6 ± 448.3 calories/day, respectively; p < 0.01), representing 102.6% and 89.7% of their DRI, respectively. In addition, the daily caloric intakes of male and female ADHD subjects were significantly higher than those of their counterparts in the control group (p = 0.04 and p < 0.01, respectively). We found significant differences between these two groups in energy intake per day attributed to the SSB consumption (327.2 ± 440.0 vs. 141.4 ± 225.2 calories/day, respectively; p < 0.01); the same observations were achieved for both boys and girls (p < 0.01 and p = 0.02, respectively). For children with and without ADHD, the average daily calories obtained from SSBs were 15.9% and 7.8%, respectively. The levels of sugar intake from SSBs of the ADHD group were significantly higher than those of the control group (296.7 ± 419.5 vs. 117.3 ± 198.1 g/day, respectively; p < 0.01).
3.4. The Association between SSB Consumption and ADHD
The crude and adjusted odds ratios (ORs) and their confidence intervals (CIs) from the bivariate analysis and multivariate analysis are shown in Table 3. The results showed a dose-response relationship between ADHD and SSB consumption. The risk of ADHD increased by 48% (OR = 1.48, 95% CI: 0.79–2.78) for children who consumed 1–6 servings/week, and the OR was 4.66 (95% CI: 2.15–10.09) for children who consumed ≥7 servings/week. These values were all significantly higher than those for children who did not consume SSBs (p for trend < 0.01). The adjusted OR showed that children who consumed 7 or more SSB servings per week had a nearly 4-fold greater odds of having an ADHD diagnosis than the reference group after other variables were taken into account (OR: 3.76, 95% CI: 1.31–10.80, p for trend of 0.02). We observed that children with higher SSB consumption had a greater risk of having ADHD.
Boys and girls reported similar SSB consumption (4.75 ± 6.90 vs. 4.29 ± 7.92 servings/week; data not shown). Because of the limited number of females with ADHD in this study (n = 25), a sensitivity analysis was performed by excluding females. A logistic regression analysis excluding females suggested that boys with ≥7 servings/week of SSB intake had a greater risk of having an ADHD diagnosis than the reference group (Table 3). The ORs were essentially the same after covariates were adjusted (p for trend of 0.06). A marginally significant dose-response relationship was also observed between ADHD and the consumption of SSB for boys after gender, consumption of milk/meat/fruit/vegetables, family history of nervous system diseases, parental education levels, maternal alcohol consumption during pregnancy, and gene polymorphism of DRD4 at rs752306 were controlled.
3.5. Gene Polymorphisms
Table S2 lists the 10 SNPs that were related to genetic variations in DRD4 and DAT1 between participants. Dopaminergic gene variations among children were evaluated as potential confounders in our study. Genetic variations of DRD4 in rs752306 were related to ADHD at p < 0.05 and were controlled in the regression model.
3.6. Lead Exposure
The collection of blood samples during participant recruitment, especially among school-aged ADHD participants, was challenging. We collected 151 blood samples (46 cases and 105 controls). The BLLs were detected in 100% of the participants because LOD was low (i.e., 0.001 µg/dL) and ranged from 0.44 to 4.71 µg/dL. The mean (±SD) of BLLs among the control and ADHD participants was similar (1.75 ± 0.77 µg/dL and 1.62 ± 0.79 µg/dL, respectively, p = 0.15). No significant difference in BLLs was found between children with and without ADHD (Figure S1). Therefore, blood sample collection was terminated.
In this case-control study, we reported that SSB consumption was associated with doctor-diagnosed ADHD. After other variables were controlled, children with greater SSB consumption had a nearly 4-fold greater odds ratio of having an ADHD diagnosis compared with those who consumed fewer SSBs, indicating a dose-response effect. Moreover, the logistic regression analysis without females suggested that males with higher SSB consumption levels were at greater risk of having ADHD, with a statistically marginal dose-response effect (p for trend is 0.06), compared with males in the control group (Table 3). This is the first case-control study to investigate the association between children's SSB consumption and ADHD diagnosis by a board-certified doctor while controlling for covariates.
Our findings are consistent with those of the limited studies that analyzed the association between SSBs and ADHD. Schwartz et al. conducted a health behavior survey and hyperactivity/inattention questionnaire on 1649 U.S. children and found that greater SSB consumption was associated with an increased risk of having ADHD [21]. A dose-response relationship between soft drink consumption and hyperactivity, as measured with a questionnaire, was found among Norwegian students even after possible cofounders were adjusted [20]. Although it did not adjust for covariates, another case-control study of 6- to 10-year-old Czech males with and without ADHD found that disruptive patterns in eating habits among children with ADHD were associated with increased consumption of SSBs [19].
The analysis of SSBs conducted in this study mainly focused on milk tea, juice or fruit-flavored drinks and Yakult drinks, which are the most popular and frequently studied SSBs in Taiwan [26,27,49,50]. The component of SSBs was gathered from the information labeled on the bottle or listed on the menu/instructions [52]. SSBs' effect on childhood ADHD may be due to the effects of sugar, AFCs, and preservatives, which are substances found in SSBs and in other foods and products. Dietary patterns established in childhood may continue into adulthood [63,64]. The type of foods sold or served in schools is an important environmental factor that contributes to children's dietary patterns, and the government should limit the availability of SSBs in schools to promote healthy eating behaviors among youth [65].
4.2. Effect of Sugar in SSBs on ADHD
Several previous studies have suggested an adverse relationship between sugar consumption (not specifically SSBs) and ADHD [7,22,66,67]. By contrast, a meta-analysis performed in the mid-1990s and mid-2010s concluded that sugar was not a proven risk factor of hyperactivity among children [18,68]. Sugar consumption is believed to cause behavioral problems because it causes: (1) sugar intolerance (discomfort experienced after eating sugar or sugary foods); (2) reactive hypoglycemia following ingestion; and (3) a reduced intake of essential micronutrients [69]. Research has suggested that the adverse effects of sugar may be due to ADHD children's inclination to consume more SSBs, but many studies have also reported the converse relationship [67,69,70]. Animal studies have also shown that prenatal sucrose consumption is a risk factor for ADHD, but this association may need to be further investigated among humans [71]. The total sugar content of popular US beverages ranged from 5.5 to 12.7 g per 100 mL [72]. The sugar content of SSBs in Taiwan was similar to that of SSBs in the U.S., ranging from 7.3 to 11.9 g per 100 mL [52]. ADHD children's sugar consumption from SSBs was significantly higher than that of control subjects (296.7 ± 419.5 vs. 117.3 ± 198.1 g/week, respectively; p < 0.01). Because SSBs are the principle source of added sugar in diets, SSB consumption may be associated with a concurrent reduction in essential nutrient intake, hypoglycemia and sugar tolerance [69,73,74]. Our study found a positive relationship between SSB intake and ADHD. Thus, public health efforts to promote healthy beverage choices and decrease SSB consumption should be actively employed.
4.3. Effects of Artificial Food Colorings (AFCs) in SSBs on ADHD
SSBs often contain other additives that could affect behavior, such as food coloring and preservatives. Some studies have shown an adverse association between AFCs and hyperactivity among children, but other results have been contradictory [6,75,76,77]. Major concerns regarding AFCs have arisen due to the composition of azo dye [78]. The top three AFCs used in food are allura red, tartrazine, and sunset yellow, representing 90% of the AFCs used [78]. The maximum allowable concentration of these three AFCs is 0.10 g/kg [4,79]. In this study, the 95th percentile AFC exposure levels for ADHD and control children were simulated by MC because this percentile was assumed to represent the worst case scenario. The estimated maximum daily AFC exposure was calculated as follows [80]:
Estimated maximum daily exposure of AFCs (mg/day/kg b.w.) = 95th percentile from MC simulation of levels of SSB consumption (servings/day) × volume of one serving (kg/serving) × maximum allowed concentration of AFCs (mg/kg)/children's body weight (30 kg) × percentage of beverages with AFCs (31%)
The margin of safety (MOS) used for the health risk assessment in Table S3 was calculated by dividing the ADI by the estimated maximum daily exposure. The MOSs for the worst case scenario among ADHD and control groups were all greater than 1, indicating no concern of incurring any appreciable health risk. Our estimated exposure to AFCs, 0.97–1.93 mg/day/kg b.w. is in line with those found in several studies. In Germany, although the SSBs that children consumed contained different colors, the mean intake of AFCs was 0.16–0.50 mg/day/kg b.w. [80]. In an Irish survey, the mean intake of AFCs was 0.39–2.77 mg/day/kg b.w., which was well below the ADI for children. For Australian children aged 6–12, the dietary exposure to AFCs was also below the ADI, even among those in the 90th percentile exposure level [81]. In the past 50 years, the daily consumption of AFCs per capita has increased 4-fold [4]. Although the exposure to AFCs reported in these studies was below the ADI, we suggest that children's exposure to AFCs should be minimized until the safety of AFCs can be refined.
4.4. Effect of Preservatives in SSBs on ADHD
Preservatives in children's food and beverages have also been reported to influence their hyperactive behavior and ADHD symptoms [5,76,82,83]. Benzoic acid (BA) and sorbic acid (SA) are often added to drinks as preservatives in the form of sodium or potassium salts [84,85], and they have a maximum acceptable beverage concentration of 1.0 g/kg [53]. The maximum permitted amount of BA and SA in SSBs is 1.0 g/kg. Thus, the 95th percentile of preservative exposure from SSBs was 62.40 mg/day/kg b.w. for ADHD children and 31.54 mg/day/kg b.w. for control children. In the worst case scenario, the MOSs for the ADHD and control groups were smaller than 1, which should be of great concern (Table S4). In our study, the estimated maximum exposure of BA and SA in the worst case scenario was much higher than that found in studies conducted in other nations [5,77]. Therefore, to raise awareness of preservative exposure through SSBs and its health implications, the allowable preservative concentration in SSBs should be lowered.
4.5. The Relationship between Dietary Habits and SSBs
We found that high maternal and paternal levels of education were associated with a decreased risk of ADHD (Table 1). This finding is in line with previous results indicating that low parental education levels are positively associated with ADHD [86,87,88]. The higher parental level of education among the control group may confer economic advantages, such as healthier meals. Therefore, these children ingest more vegetables and fruits [89,90]. Our study is consistent with the 2011 study conducted by Howard that revealed that an "unhealthy", Western-style diet (i.e., more meat and sweets and fewer vegetables and fruits) was associated with ADHD [91]. Families with high educational levels likely pay more attention to the child's alimentation, and such attention may play a protective role in children's neurodevelopment [24]. On the contrary, parents with low educational levels have been shown to be less organized in terms of alimentation habits [92]. Their children might also engage in less organized activities, cognitive tasks and cultural communication, potentially increasing these children's risk of developmental problems [93].
The caloric intakes were 102.6% and 89.7% of the DRI for children with and without ADHD, respectively. In this study, children without ADHD seemed to consume fewer calories than the DRI. Although the potential causal link between diet and ADHD is controversial, nutritional education programs for patients and/or their families should be considered.
The World Health Organization (WHO) has proposed that the proportion of daily calories obtained from sugar should be 10% or less [25]. In Taiwan, the average percentage of caloric intake from SSBs among school-aged children was 7.1% [62], which is consistent with our reported intake among children in the control group (7.9%). However, in our study, ADHD children consumed 15.9% of their daily calories from SSBs, which exceeds the recommended levels of the WHO and is quite concerning. In Taiwan, according to the new nutrition labeling requirement launched on July 1st of 2015 [94], sugar content should be labeled on packaged foods. Therefore, children, especially those with ADHD, should receive further education to inform them of the nutrition information on the label, to aid their drink selection, and to prevent their unintended overindulgence of sugar.
4.6. Children's Exposure to Lead in Taiwan
Low-level lead exposure, even at concentrations much lower than the previous action limit of 10 µg/dL (currently tightened to 5 µg/dL), has been associated with the clinical diagnosis of ADHD in several recent studies [95,96,97]. We observed no significant difference in BLLs between the two groups (1.75 ± 0.77 µg/dL and 1.62 ± 0.79 µg/dL, respectively; p = 0.15). The BLLs in this study were lower than those reported in the other two Taiwanese studies [98,99]. Since 2000, leaded gasoline has been banned in Taiwan. Additionally, 97.1% of the participants in the present study lived in the Greater Taipei area, which has low pollution levels and tight control of industrial emissions. The above reasons may explain the lower BLL measurements in our study compared with those in studies performed in 2002 and 2012.
4.7. Strengths and Limitations
This study has a number of strengths. This is the first case-control study to evaluate the association between SSB consumption and ADHD among children while adjusting for covariates. Moreover, the SNAP-IV questionnaire, a tool with acceptable reliability, was used to screen children suspected to have ADHD. Patients with an ADHD diagnoses were confirmed through extensive evaluations based on the DSM-IV-TR and performed by pediatricians or psychiatrists. This made our confirmation of ADHD cases more stringent than studies that used an interview with a student, parent, or teacher to ascertain ADHD diagnostic status [20,25,67]. Thus, the likelihood of misclassification between the ADHD and non-ADHD groups was minimal. We were also able to examine and control for known possible confounders, including dopamine-related gene polymorphisms, lead exposure, several socioeconomic indicators, and mother and child lifestyle factors, in our multivariate analyses.
However, this study also has limitations. Recall bias of participant characteristics, such as prenatal tobacco and alcohol exposure and family history of nervous diseases, likely impacted our study. We attempted to minimize recall bias by requesting information that did not heavily depend on memory or subjective interpretation, such as parental education level and maternal age at birth. Additionally, because this study did not select participants based on SSB consumption, the likelihood of selection bias was low. Another limitation is that this study did not conduct experiments on the relationship between increased intake of SSBs and the severity of ADHD symptoms. Whether increased intake of SSBs worsens ADHD symptoms or restricted intake of such beverages could reduce ADHD symptoms remain unknown. Moreover, due to quantification difficulties, we did not include the consumption of other foods or processed foods that may contain sugar, AFCs and preservatives, such as cookies, candy and sweets, in the questionnaire. Furthermore, foods with additives, such as monosodium glutamate (MSG), which might increase the risk of having ADHD, were not included in the questionnaire. Considerable clinical and experimental evidence suggests that deficiencies or imbalances in certain micronutrients, such as vitamins A, C, D, B6 and minerals may contribute to ADHD [24,100,101,102]. However, information on micronutrient status is not available in this study. Because the subjects in this study live in the municipal greater Taipei area, the likelihood that they consume insufficient micronutrients is minimal. Further studies on the relationship between micronutrient status and ADHD are needed in Taiwan.
In this case-control study of Taiwanese children, a dose-response relationship was found between SSB intake and ADHD. This association remained unchanged after gender; consumption of milk, meat, fruits, and vegetables; parental education level; maternal alcohol consumption during pregnancy; family history of nervous system disease; and DRD4 genetic variations in rs752306 were controlled. In this case-control study, we have shown an association between SSB consumption and ADHD. However, we cannot demonstrate causality. The consumption of SSBs might be a consequence rather than a cause of ADHD. Future research should explore the direction of and the mechanisms underlying this association.
The following materials are available online at www.mdpi.com/1660-4601/13/7/678/s1, Figure S1: Boxplot diagram of BLLs for ADHD and normal control participants, Table S1: Relationship between maternal education level and smoking/alcohol consumption during pregnancy, Table S2: Polymorphism of dopamine-related genes (DRD4/DAT1) of the study participants, Table S3: Frequently used artificial food colorings (AFCs) and estimated dosage, Table S4: Frequently used preservatives and estimated maximum exposure.
We are thankful for the financial support provided by the Department of Health, Taipei City Government, and Aiming for the Top University Plan from the Ministry of Education of the Republic of China, Taiwan. The work was also supported by grant NSC 96-2314-B-010-020-MY3 from the National Science Council of Taiwan. We also acknowledge the High-throughput Genome Analysis Core Facility of the National Core Facility Program for Biotechnology, Taiwan (MOST 103-2319-B-010-001) for SNP genotyping. This manuscript was edited by American Journal Experts.
Ching-Jung Yu, Jung-Chieh Du, Chun-Cheng Feng, Winnie Yang, Ming-Yi Chung, Ying-Sheue Chen, Betau Hwang and Mei-Lien Chen conceived and designed the experiments; Ching-Jung Yu, Jung-Chieh Du, Hsien-Chih Chiou, Chun-Cheng Feng, Ying-Sheue Chen and Ling-Chu Chien performed the experiments; Ching-Jung Yu, Jung-Chieh Du, Chun-Cheng Feng and Ling-Chu Chien analyzed the data; Ling-Chu Chien and Mei-Lien Chen contributed reagents/materials/analysis tools; Ching-Jung Yu and Mei-Lien Chen wrote the paper.
The authors declare no conflict of interest. The founding sponsors played no role in the design of the study; the collection, analyses, or interpretation of the data; the writing of the manuscript; or the decision to publish the results.
The following abbreviations are used in this manuscript:
ADHD Attention deficit/hyperactivity disorder
SSB Sugar-sweetened beverage
DRD4 D4 dopamine receptor gene
DAT1 Dopamine transporter gene
AFC Artificial food coloring
DSM-IV-TR Diagnostic and statistical manual of mental disorders, 4th edition, revised criteria
BLL Blood lead levels
SNAP-IV Swanson, Nolan and Pelham, fourth revision
MOHW Ministry of Health and Welfare
TFDA Taiwan Food and Drug Administration
LOD Limit of detection
MC Monte Carlo
OR Odds ratio
CI Confidence interval
ADI Acceptable daily intake
MOS Margin of safety
BA Benzoic acid
SA Sorbic acid
WHO World Health Organization
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Figure 1. Mean consumption (95% CIs) of SSBs among controls and children with ADHD (unit = servings/week).
Table 1. Demographic characteristics of the study participants (N = 332).
n = 159
Demographic characteristics
Gender (%) <0.01 *
Female 68 (42.8%) 25 (14.5%)
Male 91 (57.2%) 148 (85.5%)
Body weight 32.1 ± 11.6 33.8 ± 12.3 0.20
Age (years) 8.9 ± 2.0 9.2 ± 2.7 0.31
Gestational age at birth (%) 0.34
<37 weeks 15 (9.4%) 22 (12.7%)
≥37 weeks 144 (90.6%) 151 (87.3%)
Parity (%) 0.80
Primiparous 87 (54.7%) 97 (56.1%)
Multiparous 72 (45.3%) 76 (43.9%)
Birth Order (%) 0.87
1st 87 (54.7%) 93 (54.7%)
2nd 56 (35.2%) 57 (33.5%)
3rd and above 16 (10.1%) 20 (11.8%)
Paternal education level (%) <0.01 *
High school or below 39 (24.5%) 98 (56.6%)
College or advanced training 120 (75.5%) 75 (43.4%)
Maternal education level (%) <0.01 *
Family history of nervous system diseases (%) 0.02 *
No 130 (81.8%) 123 (71.1%)
Yes 29 (18.2%) 50 (28.9%)
Maternal age at birth 30.3 ± 4.4 30.1 ± 5.0 0.80
History of still or dead birth (%) 0.17
Smoking during pregnancy (%) 0.50
Yes 9 (5.7%) 13 (7.5%)
Alcohol consumption during pregnancy (%) <0.01 *
Yes 7 (4.4%) 22 (12.7%)
Chronic disease during pregnancy (%) 0.16
Yes 12 (7.5%) 21 (12.1%)
* p < 0.05.
Table 2. Dietary characteristics of the study participants (N = 260).
Dietary habits
Total SSBs consumed (servings/week) <0.01 *
3.10 ± 5.08 6.96 ± 9.27
Categorized SSB consumption (servings/week) <0.01 *
0 51 (32.1%) 19 (18.8%)
1–6 89 (56.0%) 49 (48.5%)
≥7 19 (11.9%) 33 (32.7%)
Milk tea (%) <0.01 *
0 104 (65.4%) 52 (51.5%)
≥7 4 (2.5%) 12 (11.9%)
Juice or fruit-flavored drinks <0.01 *
≥7 1 (0.6%) 6 (5.9%)
Yakult drinks <0.01 *
Other SSBs 0.11
Rice/Noodle (servings/week) 20.53 ± 5.30 20.42 ± 4.62 0.34
Meat (servings/week) 14.02 ± 9.98 18.14 ± 13.89 0.04 *
Milk (servings/week) 3.33 ± 2.93 5.01 ± 5.02 0.02 *
Eggs (servings/week) 4.32 ± 2.78 4.43 ± 3.01 0.77
Vegetables (servings/week) 16.61 ± 12.64 11.97 ± 9.04 <0.01 *
Fruits (servings/week) 5.70 ± 3.61 4.78 ± 3.68 0.02 *
Fish (servings/week) 5.92 ± 7.74 6.66 ± 8.22 0.65
Shellfish (servings/week) 1.98 ± 3.24 1.92 ± 3.08 0.79
Other types of seafood (servings/week) 1.12 ± 1.86 1.36 ± 2.32 0.94
Caloric intake (day)
From foods other than SSBs 1660.2 ± 352.2 1733.9 ± 386.6 0.07
From SSBs 141.4 ± 225.2 327.2 ± 440.0 <0.01 *
Total calories 1801.6 ± 448.3 2061.1 ± 689.7 <0.01 *
Total calories 1797.7 ± 482.0 2265.0 ± 897.5 0.04 *
From SSBs 158.4 ± 236.9 292.1 ± 395.2 0.02 *
Ingested sugar from SSBs (g/week)
117.3 ± 198.1 296.7 ± 419.5 <0.01 *
Table 3. Crude and adjusted odds ratios for the association between sweetened beverage consumption and ADHD (N = 260).
Adjusted 1
(A) All subjects <0.01 * 0.02 *
0 Reference Reference
1–6 1.48 (0.79–2.78) 1.36 (0.61–3.05)
≥7 4.66 (2.15–10.09) 3.69 (1.291–10.60)
(B) Boys only 0.01 * 0.06
≥7 3.61 (1.47–8.88) 3.54 (1.057–11.95)
1 Adjusted covariates: gender, consumption of milk/meat/fruit/vegetables, family history of nervous system diseases, parental education levels, maternal alcohol consumption during pregnancy, gene polymorphism of DRD4 at rs752306; * p < 0.05.
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Yu, C.-J.; Du, J.-C.; Chiou, H.-C.; Feng, C.-C.; Chung, M.-Y.; Yang, W.; Chen, Y.-S.; Chien, L.-C.; Hwang, B.; Chen, M.-L. Sugar-Sweetened Beverage Consumption Is Adversely Associated with Childhood Attention Deficit/Hyperactivity Disorder. Int. J. Environ. Res. Public Health 2016, 13, 678. https://doi.org/10.3390/ijerph13070678
Yu C-J, Du J-C, Chiou H-C, Feng C-C, Chung M-Y, Yang W, Chen Y-S, Chien L-C, Hwang B, Chen M-L. Sugar-Sweetened Beverage Consumption Is Adversely Associated with Childhood Attention Deficit/Hyperactivity Disorder. International Journal of Environmental Research and Public Health. 2016; 13(7):678. https://doi.org/10.3390/ijerph13070678
Yu, Ching-Jung, Jung-Chieh Du, Hsien-Chih Chiou, Chun-Cheng Feng, Ming-Yi Chung, Winnie Yang, Ying-Sheue Chen, Ling-Chu Chien, Betau Hwang, and Mei-Lien Chen. 2016. "Sugar-Sweetened Beverage Consumption Is Adversely Associated with Childhood Attention Deficit/Hyperactivity Disorder" International Journal of Environmental Research and Public Health 13, no. 7: 678. https://doi.org/10.3390/ijerph13070678
Supplementary File 1:
Supplementary (PDF, 144 KiB)
Int. J. Environ. Res. Public Health, EISSN 1660-4601, Published by MDPI

redpajama_set_name: RedPajamaCommonCrawl


Brian Hess is the co-owner of Hess Roofing, a family owned San Diego roof installation and repair company.
Knowing he has an addictive personality, Brian explains how he used drinking as a way to mask other issues.
Brian describes negative influences as "windsocks" that keep you from being in a happier place.
Being able to truly appreciate himself, Brian shares how invaluable it is to have the support of his loved ones.
How Brian is using meditation to further improve his life and his golf game.
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Dream Center of Tampa
Lead Pastor, Craig Altman, of Grace Family Church founded Dream Center of Tampa. The church's vision to reach youth and families in need led it to build the center. It is located at 2806 North 15th Street, in Tampa.
Renovations on the 19,000 square foot facility began in November 2010. With the help of hundreds of volunteers from Grace Family Church, Open Arms Church, Sisters Making a Difference, Jed Kirby & Urban Young Life, and area businesses, such as Cornerstone Construction, Simpson Environmental, KB Partner Foods, Aaron's Incorporated, Mandy's Electric, KDS Interiors, Hugh MacDonald Roofing, and Total Solutions, the building completed its transformation and opened the doors in August 2011.
Government cutbacks have diminished access to programs and resources for people in East Tampa, and families were anxiously awaiting the opening of the Dream Center. Services offered include after school care, computer access and tutoring, mentoring and family counseling, job and skills training and sports activities.
Upcoming events include the monthly Adopt-A-Block, wherein volunteers meet on the 2nd Saturday of each month to go into the community to help neighbors with projects in and around their homes and to pray for them. The next event will be July 11, 2015.
On July 15, 2015, Teddy Dupay, Florida's all-time leading basketball scorer and current youth coach, will attempt to break multiple world records for the most basketball 3 pointers. According to the Guinness Book of World Records, the current world record is 10,381 in 24 hours. The event is open to the public. All proceeds will benefit Academy Prep Center of Tampa and St. Petersburg, a non-profit school dedicated to educating economically disadvantaged middle school students.
Volunteers are needed at the Dream Center of Tampa for afterschool group mentoring for grades K-5 (computers, arts and crafts, recreation, homework help, and athletic programs for grades K-12, Boys Mentoring program, Girls Mentoring Program, and more. If you are interested in volunteering or mentoring, please go to http://dctampa.org/get-involved/.
You can support the Dream Center by purchasing a coupon book from any of these participating stores. A portion of the proceeds benefits the Dream Center of Tampa Bay.
http://dctampa.org/pdf/coupon-book-list.pdf
Church services are held at Dream Center of Tampa on Sundays at 11:30 am. The services are taught by Lead Pastor, Craig Altman, with contemporary Christian music, fun teaching for your children, and the dress is casual. Ralph J.E. Johnson is the Campus Pastor, and he can be reached at (813) 374-8999 or via email at rjohnson@dctampa.org.


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Bruno Mars and the appropriation of Black music
by Daren W. Jackson · Published June 25, 2017 · Updated June 26, 2017
In the wake of major cultural success, many have celebrated Bruno Mars for "bringing back funk". But just like when Prince threw shade at Justin Timberlake for claiming to bring sexy back, funk never left. The truth is that Bruno Mars is actively appropriating Black culture. I've outlined the reasons why and how he keeps getting a pass for it.
When I heard that Bruno Mars was set to open the 2017 BET Awards, I couldn't help but feel some kinda way. Not that I haven't enjoyed his music. Not that I don't recognize his talent. My issue is that a non-Black singer who appropriates Black culture and sounds was scheduled to open the biggest celebration of Black music for the entire year.
If you are like many people on social media, that statement alone has you deep in your feelings. So pause a second and take some deep breaths. Let your blood pressure return to normal. Now read on and understand how sinister (purposefully or not) Bruno Mars is to Black artists.
The Evolution of Bruno Mars
First things first, let's stop pretending as if Bruno Mars has been a champion for Black music his entire career. As a child, Bruno Mars was an Elvis impersonator in his father's rock & roll review, even appearing in Honeymoon to Vegas with Nicolas Cage. Funny how he was raised impersonating one of the most notorious appropriators of Black music in history, only to follow in his footsteps.
His first album, Doo-Wops & Hooligans, made pop music out of heavy usage of Doo-Wop conventions. You can't tell me that's not what "The Lazy Song" and "Marry You" were. His second album, Unorthodox Jukebox, started his partnership with Mark Ronson as well as his funk influences. And then came "Uptown Funk" and his 24K Magic album. Both dove right into using funk and other historically Black musical genres as their basis. And the appropriation evolution was complete.
My claims aren't unfounded or even outside of the mainstream. Even top music magazine Billboard reviewed his most recent album with a track-by-track listing of the artists he used as "inspiration". It is no secret that Mars leans heavily on the past for his music. So much so, that many of his songs are sonically undiscernable from the songs and artists he "credits".
The Legal Cases Against Bruno Mars
Beyond claims of appropriation, there are legal actions being taken against Bruno Mars as well. Just like "Blurred Lines", some of the artists who Mars claims as his inspirations see his music as theft
The Gap Band took issue with "Uptown Funk", claiming it borrowed from their "Oops Upside Your Head". In the end, they were granted 17% of all publishing royalties.
Serbian artist Snezana Miskovic (who sings under the name Viktorija) made similar claims against "Uptown Funk". And after a listen to the songs side-by-side, I can't disagree.
Collage attacked the song as well, saying it is just like their song "Young Girls".
Argentine rock legend Charly Garcia claims the same for his song "Fanky" (though I think this comparison is as obvious)
Angie Stone and former members of the Sequence have also accused Mars and Ronson of stealing their sounds
And the list goes on and on. Radio.com even put together a list of 8 artists who could sue on similar grounds.
This is by no means meant to be an exhaustive list of all the legal challenges thrown at Mars. This illustrates that what Bruno Mars might call an homage many artists see as a thinly-veiled copy. And if these artists themselves take issue with it, why are we so quick to give him a pass?
The Weakness of Giving Credit
Many are quick to refute the belief that Bruno Mars is appropriating Black music because he gives them credit. And as proof, they always point to his recent feature in Latina magazine.
But this quote only acknowledges that Bruno Mars understands the roots of the music he makes. It does not address the fact that he is profiting off of the cultural expressions of Black people. In fact, it read more like a means for him to defend his actions. If we agree with him that all music is Black music, then our music is pretty much up for everyone's use. By giving us "credit", he both honors our efforts and provides cover for him to continue profiting from them.
Trending on Twitter
This conversation spilled onto Twitter and trended for hours today. After just broaching the subject, our own EIC Jenn M. Jackson faced a deluge of "Hooligans" (the moniker chosen by Bruno Mars superfans) with clutched pearls of outrage. Honestly, we spent the day leisurely hanging out with family, not all that invested in the conversation. But by the afternoon, her tweets had received millions of impressions and even drew the ire of a member of the singer's band. TheWrap.com even posted a write-up about it (without reaching out to her for comment or using her actual name, as most outlets would do).
Just imagine if all of those furious Twitter users around the world mobilized for something like #BlackLivesMatter or social justice or any of the major issues the world is facing in this moment.
But in all of the conversation and criticism (much of it devolving into misogynistic, racist, and superficial hatred), no one was able to defend Bruno Mars from three simple points: 1) Bruno Mars does not self-identify as Black; 2) he receives a pass where other do not (likely because of patriarchy); and 3) giving credit to other artists isn't enough.
I'd argue that as someone who has so publicly stated that his work is inspired by others, Bruno Mars should be working to advocate for the genre. Yet he seems far more interested in defending and advocating for himself.
Let's Think Critically About Bruno Mars
Blackness is not open and available to anyone's use. In most cases, Black folk have become hyper-vigilant about protecting our cultural heritage. But for some reason, many have nothing to say about Bruno Mars. Maybe it's because they think he is Black. Maybe it's because they just really like his music. Or maybe it's because they just haven't thought critically about what his place in the music industry actually means. I sincerely hope that those people read this article, and whether they agree or disagree, can come to better understand.
If Bruno Mars were Black-identifying, no one could criticize him for creating Black music. It'd be his birthright, for better or for worse. But Mars does not identify that way.
So why do so many people cape for him? My best guess is patriarchy and anti-Blackness. Why else would he get invited to the cookout while Iggy Azalea and Katy Perry have been almost universally shunned? Maybe their being white has some influence here. But, let's not forget, Robin Thicke and Justin Timberlake only got dropped from the cookout after a couple years on the guest list. It's time to rescind Bruno Mars's invite too.
Yes, Black people created all the best styles of music. That doesn't mean that you have to steal it. Better yet, don't just copy (or worse, water down) what has been successful or groundbreaking before. Do something that is uniquely you.
Want More Convos Like This One?
January 27, 2014 The Grammys Are For White People
June 27, 2017 6 Funk Artists Bruno Mars Can't Hold A Candle To
November 23, 2016 Bruno Mars Must Be Stopped – '24K Magic' Album Review
June 27, 2016 10 Best Responses To Justin Timberlake Trying To Be Black Again
February 12, 2013 The Boss Moments and Epic Failures of the 2013 GRAMMYS
December 10, 2013 On Rashida Jones, the 'Pornification of Everything', and 'Slut Culture'
Co-Founder/Editor
Daren is one half of the Water Cooler Convos team. He's a writer, music connoisseur, and comic book geek who spends his free time working on his novel and other short stories.
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ABC doesn't deserve kudos for canceling 'Roseanne' - May 29, 2018
An open letter to Donald Glover, Childish Gambino, and his anti-Black "This Is America" video - May 14, 2018
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Tags: appropriationBruno MarsCharly GarciaCollagecultureGap BandMark RonsonViktorija
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Marie-Anne de Roumier-Robert was an 18th-century French writer. She wrote one of the earliest known works of science fiction, Voyage de Milord Céton dans les Sept Planètes ("Lord Seton's Voyage Among the Seven Planets", 1765).

References

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18th-century French women writers
French feminist writers
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French women novelists

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Where to live stream Uruguay vs France online in the USA
Natalie Shepel
Posted: 5 July 2018 8:45 pm News
We've tracked down where to stream Uruguay vs France in the USA so you don't miss a minute of the action.
France and Uruguay kick off the World Cup quarterfinals, with both teams in great spirits following their resounding victories in the Round of 16.
MUST READ: The FIFA World Cup 2018 streaming guide
France put up an unconvincing performance in the first stage of the World Cup, but topped their group nonetheless with 7 points. They got their groove back in the Round of 16, after a thrilling clash with Argentina. It was a match for the ages, with seven goals and plenty of excitement worthy of a knockout round.
Antoine Griezmann opened the scoring in the 13th minute, converting a penalty, but the South Americans were quick to equalize via Angel Di Maria about half an hour later. Argentina briefly took the lead in the 48th minute thanks to a goal by Ever Banega. The second half, however, belonged to France, who put on a major tour de force and scored three goals in about 10 minutes. Benjamin Pavard was first to find the net in the 57th minute, with Kylian Mbappe then scoring two times in quick succession. Argentina scored again via Sergio Aguero in the final minutes, but it wasn't enough to avoid elimination. Fun fact: Mbappe was born just a few months after France won their only World Cup title in 1998.
Meanwhile, Uruguay topped Group A with three victories and went on to beat Portugal in the Round of 16. They eliminated the Europeans thanks to two goals from Edison Cavani, With Portugal only finding the net once, via Pepe. It was a hard-fought win, but Cristiano Ronaldo & Company never really got going in the tournament, as the team relied way too much on their star player. France should prove a much tougher adversary overall.
As far as the two teams go, Uruguay have concerns lingering over Edinson Cavani, who sustained a hamstring strain. France should be in tip-top shape. The two former world champions will go head to head at Nizhny Novgorod.
Uruguay vs. France: Kick off time and date
The knockout match kicks off at 10 a.m. ET on Friday, July 6, 2018.
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Portugal's Fernando Santos bemused by Danilo Pereira's inexplicable rib injury
PA Sport Staff
November 27, 2022, 2:24 p.m. ·3 min read
Portugal boss Fernando Santos admits he has been left baffled by the rib injury sustained by Danilo Pereira in training ahead of Monday's World Cup clash with Uruguay.
A statement on the Portuguese Football Federation's official website on Saturday said the Paris St Germain player was unavailable having "suffered a fracture of three costal arches".
Santos told a press conference on Sunday: "That's a type of injury that no-one can explain. We do not understand how that could have happened.
"It's normal that these type of injuries happen, but we did not see how it happened exactly.
"Initially we did not think it was very serious, because we made a few exams to see if he was breathing properly and apparently that was the case, but afterwards we see that it was more serious than we expected. But we are following it up.
"I'm not a medical doctor, I cannot talk about that in detail. But as far as I know he is evolving positively and we expect to have him very soon in the field of play – but in case we cannot, we have three other players who can replace him. So we do not need to make any drama.
"We are very sad because of his injury. Now we're thinking about his health and I think above all we need to think about a player as a human being.
"He's someone with a very positive energy and I'm sure he'll be sending good vibes our way."
Pereira's team-mate Bernardo Silva said: "We're very sad for him, but it also is an additional driver for all the team-mates to play to win and to be able to dedicate this win against Uruguay to Danilo, because not only is he a great player but he's a fantastic person and a player we'd really like to have on the pitch with us."
Portugal are looking to extend a winning start in Group H after opening their campaign by beating Ghana 3-2 on Thursday, a match which included a goal from Cristiano Ronaldo that made him the first player in the men's game to score at five World Cups.
Uruguay's opener saw them draw 0-0 with South Korea, and boss Diego Alonso said: "We would have loved to win in the first match, that's for sure, but we cannot underestimate the opponent, we cannot underestimate the result we had either.
"We are here to win games, that's our ultimate goal, and we want to give our best. But at the same time we know in a competition it is difficult, that you need to bring your best and sometimes even if you perform well (or not), anything can happen.
"Of course Portugal have a very good squad, excellent players, a wonderful coach with wide experience. They're a dangerous team. But on the other hand we also have our own arguments, our own weapons. We will try to win. We will bring our 'A' game. Lets see what happens."
Uruguay, under Alonso's predecessor Oscar Tabarez, beat Portugal 2-1 in the last 16 of the 2018 World Cup – Alonso stressed when asked about that that "all matches are different". Portugal are currently ninth in the world rankings, while Uruguay are 14th.
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Climate-KIC's Alumni Association will present itself during a 30-minute "Speaker's Corner" style event.
The event will take place at the Grand Palais in central Paris, Solutions Corner, from 14:45 – 15:15.
The Climate-KIC Alumni Association (CKAA) is a European society of professionals from an interdisciplinary network founded to inspire the entrepreneurial soul in Europe to create a climate-resilient society.
What makes the CKAA unique are the development of activities aiming to enable and facilitate the transfer of knowledge and skills within the CKAA and beyond. This approach aims to generate systemic change by encouraging and empowering our members to keep pushing boundaries in the fight against climate change.
Currently the association gathers 1,200 members from interdisciplinary backgrounds. The corner aims to share some of the many activities and projects of the CKAA.


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Q: how to calculate the amount for total hours in javascript i need to calculate the work in the hourly base, for one hour I spent 100 Rupee means, my total amount will 100 Like that i need to calculate the hours to amount in javascript. example code
var timeSpent = 1:25:58, //1:26
    amountPerhours = 100;

how to calculate the total amount based on working hours in javascript

A: You could get first the decimal representation of the time and multiply it then with the hour factor. Later you might add some fixing.

var timeSpent = '1:25:58',
    amountPerHour = 100,
    time = timeSpent
        .split(':')
        .reduce((r, a, i) => r + a * Math.pow(60, -i), 0),
    result = time * amountPerHour;

console.log('time', time);
console.log('amount', result.toFixed(2));

A: Try to split your input variables:
var hours = 3;
var minutes = 25;
var seconds = 58;
var amount = 100;

var result = hours*amount + minutes*amount/60 + seconds*amount/3600;

A: Try this:

function getAmount(timeSpent) {
    var amountPerhour = 100;
    var time = timeSpent.split(":");
    var hours = time[0];
    var mins = time[1];
    var secs = time[2];

    if (secs != undefined && secs > 29) {
        mins++;
    }
    var amount = (+hours + +mins/60) * amountPerhour;
    return parseFloat(amount).toFixed(2);
}

console.log(getAmount("1:25:58"));

A: The amount can easily be calculated in one line. Refer to the below snippet.

var time = "1:25:30";
var amount = time.split(":")
    .map((a,b) => a/(60**b))
    .reduce((a,b) => a+b)
    .toFixed(2) * 100;
console.log(amount);

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